Keywords: Avionics and on-board equipments
Abstract: Starting in 1974, with airplanes ranging from the A300, to the A380, the A350 XWB, and the A320/A330neos, Airbus delivered its 10,000th aircraft in October 2016. The aviation sector is expanding; passenger demand doubles every 15 years. By 2050, the air transport industry could be handling up to 16 billion passengers and 400 million tons of cargo annually. Passengers have also become increasingly mindful of the ecological impact of their travel choices and are asking for more comfort and connectivity. Flying more safely, more simply, but also fully respecting environmental targets are our growing challenges. In addition, the design of space systems faces increasingly aggressive worldwide competition, with continuously changing and more demanding markets, calling for reliable, efficient, and new control design tools and technologies, compatible with reduced development cycles. In this context, some future aerospace challenges will include the reduction of the system complexity while maintaining the same high-level safety standards. Efficient systems’ architectures must be designed with this in mind. Distributed architectures are promising, not only at aircraft or satellite level, but as part of a “system of systems”, connecting all aerospace operations’ stakeholders. Digitalisation is also transforming the way our industry operates, creating numerous opportunities to decrease development cycles whilst increasing maturity and level of confidence. And from the customer perspective, predictive maintenance, fault detection, diagnosis and prognostics are key to improving operational reliability and the overall performance of Airbus products.

Keywords: Large Scale Systems Effects, Systems Theory
Abstract: Soft robots present several advantages. However, one of the main challenges of this new field of robotics is to control these robots. The methods used to control rigid robots are not directly relevant and new approaches have to be invented or updated to be applied to this kind of robots. This paper introduces control solutions for soft robots studies taking into account dynamics of the system.

Keywords: Econometric methods, Econometric models, Game theories
Abstract: In-flight loss-of-control (LOC-I) still poses a severe threat to today's commercial aviation. Hence, we review the literature for non-linear analysis and control methods of LOC-I and upset recovery. Using state-of-the-art methods such as continuation theory and reachability estimation, we sketch an analysis of an aircraft's flight envelope in terms of its trim conditions and propose control approaches both within and outside the envelope.

Keywords: University-industry cooperation for training control engineers, University-industry co-operation in control engineering education
Abstract: This paper emphasizes several dynamical aspects of a quadrotor induced by propellers inertia, especially when its rotors are tilted or asymmetrically distributed around its body. To achieve this, a simplified linear model is established for a generic quadrotor and successively applied in three cases: a flat and symmetric quadrotor, a V-shaped quadrotor and finally an asymmetric quadrotor. The results are illustrated via numerical simulations.

Keywords: Socially desirable requirements for automation development, Human-centered systems engineering
Abstract: This work proposes a design methodology for an observer-based impact detection with serial robot manipulators in presence of modeling uncertainties and using only proprioceptive sensors. After expressing modeling errors as the contribution of both dynamic parameters uncertainties and numerical differentiation errors, a Kalman filter is designed based on the inverse dynamic model with process and measurement power spectral densities explicitly depending on characterized uncertainties. The influence of the design parameters on the quality of the external torque estimation is studied in simulation and guidelines for tuning the Kalman filter are provided.

Keywords: Telemedicine
Abstract: Medicine requires advanced teaching methods in order to reach an efficient student training without having to train them directly on patients. In France, the Haute Autorité de la Santé (H.A.S.) has stated to "never [do] the first time with a patient" as a requirement for the training of new doctors. The goal of this work is to offer a novel robotic solution to teach students how to perform an epidural anaesthesia. This medical operation can be divided into two different gestures: first the insertion of a needle between two vertebrae and second the application of pressure on the plunger all along the insertion of the needle. This works aims at simulating this second part as it has already been done on the first part in previous studies. We introduce a way to emulate the principle of loss of resistance felt by the anaesthetist when the needle reaches the appropriate depth.

Keywords : Simulators, Nonlinear control system

Keywords: Control education using laboratory equipment, University-industry co-operation in control engineering education, Complexity modelling
Abstract: Ballistic testing of flying vehicles, such as space probes or projectiles, is an important part of their design. The model describing the behaviour of a vehicle in free flight is nonlinear, characterised by the off-equilibrium dynamics and absence of the input signal. This paper presents the construction of a linear parameter varying (LPV) model describing the behaviour of a re-entry space probe in flight. The difficulties of this task reside in a lack of available trimming procedure, treated in the literature as a usual prerequisite for the LPV modelling, and a high dimension of the scheduling parameter vector. Two modelling techniques were applied: the velocity-based method and a modified version of the Jacobian linearisation method.

Keywords: Renewable Energy System Modeling and Integration
Abstract: The majority of industrial systems and specially electrical energy producing systems, depend mainly on rotating machinery. The cost of operation attracted a lot of attention with the rise of wind turbines as a powerful replacement to old fossil fuel-based, electrical energy producing, machinery. Condition monitoring stepped up as a vital systematic series of action aiming to optimize the lifetime expectancy of system components, while reducing the cost of maintenance of wind turbines. This paper will go through the numerous and various condition monitoring methods and supporting techniques used in the literature. An acumen on the importance of the Kalman Filter in tracking faults in wind turbines will be simulated and discussed.

Keywords: Enterprise Networks, Data-Driven Decision Making
Abstract: The multiplicity of existing standards and the continual introduction of new standards are producing ever greater problems on how to use these standards to keep the aircraft airworthy and safety in a more efficient way. In this paper, we first propose a MRO(Maintenance, Repair and Overhaul) process based on different stakeholders, and then an overview of the existing standards in the civil and military has been conducted for identifying the state-of-the-art standards. Finally, we analyze s-series standards mainly in five aspects that including scope, data model, interoperability, advantages and disadvantages.

Keywords: Building Automation
Abstract: For the last decade, research efforts have focused on developing strategies for improving the energy efficiency of buildings and limiting their environmental impact. In addition to the evaluation of their energy performance, energy forecasting models are essential for building energy control and operation. However, designing control strategies requires a computationally efficient model. Hence, one has to have at their disposal reliable and easy to implement models allowing to observe and predict the energy behavior of buildings in near real-time. In this work, we study the capability of switching models for modeling the thermal behavior of buildings based on the idea that, in a building system, different configurations might occur (opening/closing windows, heating on/off, etc.).

Keywords: University-industry co-operation in control engineering education
Abstract: This work concerns applied research in the field of automotive control, in particular on the control of Electric Power Steering systems (EPS) to reduce the production costs. This study is meant to design a new control strategy with less available outputs (especially without torque sensor) and preserved steering performance. Thus, two approaches could be considered: first, a driver torque estimation coupled to a conventional controller; second, a control strategy not using the driver torque information. Moreover, from the obtained controller design, an analysis of the new system shall be developed in order to draw conclusions on an appropriate mechanical structure. For this purpose, the study is performed on a column-type EPS system for which a model is expressed by Newton's law of motion. This model is validated using experimental data obtained on a prototype vehicle. Then, the control objectives are defined and potential designs of the controller are discussed, with a reminder on driver torque estimation method. The simulation environment to analyse the strategies is also described.

Keywords: Control and Automation Systems failure, Energy and Distribution Management Systems, Renewable Energy System Modeling and Integration
Abstract: In this paper, a hybrid observer for a class of DC-DC power converter is proposed. The considered class of switched system including one or several unobservable subspace. Thus,the state vector of a converter is not observable at any time. The aim is to solve this problem of observability by taking into account the hybrid dynamic behavior appearing in the converter. Such problem can be tacked by a new observability concept (Z(TN)-Observability). An application to a Single-Ended Primary Inductor Converter (SEPIC) is presented. After recalling to hybrid dynamic behavior of the SEPIC, an observability analysis is investigated. Following this analysis, a hybrid observer is designed based on homogeneous observer coupled with an estimator. Finally some illustrative results are given in order to show the efficiency of the designed observer.

Keywords: University-industry co-operation in control engineering education
Abstract: Abstract: This paper describes a classical methodology used to model and identify the parameters of an oxygen regulator with the goal of increasing its stability performance. After detailing the modeling-identification part to determine the physical parameters of the regulator and laying down the ongoing difficulties for analyzing the stability of this system, a short application of this methodology is shown.

Keywords: Energy and Distribution Management Systems, Energy Storage Operation and Planning, Systems Theory
Abstract: Lately, the meshed topology of the DC microgrids has shown increasing interest in research and industrial communities since it provides higher reliability and optimizes the performance of the system. This is achieved by reducing the power transmission losses within the DC bus. This work presents some preliminary studies on the control and optimization scheduling of a DC microgrid with meshed topology. The considered microgrid is connected to the utility grid (UG) and includes a solar panel (PV), an energy storage (ES) system, electrical vehicles (EV) and different types of DC loads such as printers or computers. Switching devices (inverters, converters, DC-breaker and the like) connect the sources and the loads to the DC bus and enable the control of the system's power transmission.

Keywords: Mobile robots, Guidance navigation and control, Identification and control methods
Abstract: In this work, an unconstrained Model Predictive Control (MPC) controller, and a filtered Smith predictor (FSP) structure are applied as a solution for a trajectory tracking problem of an omni-directional mobile robot through a networked based control scheme. The FSP is able to deal with the process dead-time, due to communication delay, and also mitigate measurement noise improving the robustness of the controller, while the control signal is calculated by simply applying the MPC explicit solution. The proposed controller uses a cascade structure where the innermost control loop is responsible for the velocity control, while the outer loop controls the position error. The performance of the controller is evaluated using experimental results when controlling the mobile robot in different trajectories.

Keywords: Guidance navigation and control, Flying robots, Modeling
Abstract: The capability of autonomous formation flight has the potential to significantly enhance the utility and efficiency of small low-cost Unmanned Aerial Systems (UAS). Formations of small, inexpensive fixed-wing UAS allow for the sharing of remote sensing functionality, mission-level redundancy and range enhancements due to aerodynamic interactions widely exploited by migratory birds. This article presents a benchmark problem for scalable distributed flight control of formations of UAS with only local relative state information, one of the open problems in this field as of today. The benchmark is openly available and comprises a nonlinear six degrees of freedom dynamics model of an electric glider UAS. In this article we furthermore introduce a nominal guidance frame that does not require state information of other UAS and point out a fundamental issue related to wake vortex tracking during formation maneuvers. A set of LQ baseline controllers that are part of the benchmark is presented along with simulation results.

Keywords: Telerobotics, telepresence, Mobile robots
Abstract: This paper presents a novel bilateral teleoperation system architecture using an admittance configured haptic interface for environmental force reflection in mobile robot teleoperation tasks. By changing the feedback point of environmental forces in a two-channel teleoperation system architecture, the proposed approach enables the environmental force reflection in an admittance configured haptic interface, which allows the commonest force based environment perception and obstacle avoidance algorithms to be implemented in the admittance configured haptic interfaces leading to users' better perception of both vehicle's motion and environmental forces. Under the new system architecture, human operators can perceive vehicle's dynamic motion in free flight, or simultaneously both the dynamic motion and environmental forces in obstacle strewn environments, which can not be achieved by the classical admittance or impedance configured haptic interface. In addition, the novel approach is also capable of facilitating obstacle avoidance without inducing potential instability as other force based obstacle avoidance algorithms may do. Analysis on transparency and stability were conducted based on the previously developed teleoperation system. Both simulation and experimental study were undertaken to verify the effectiveness and performance of the proposed scheme using a haptic joystick. The outcomes of simulation and experiments confirm the authors' claims that the proposed approach provides intuitive perception of vehicle's motion and environmental forces, as well as facilitates navigation and obstacle avoidance in the mobile robot bilateral teleoperation system.

Keywords: Flying robots, Guidance navigation and control, Design methodologies
Abstract: This paper presents a coordinate-free trajectory tracking control design for the nonlinear dynamics of a variable pitch quadrotor. Unlike conventional quadrotors, the rotor thrust is varied by changing its blade pitch angle as opposed to its RPM. It has been shown that such an actuation mechanism has a very high control bandwidth and is capable of producing negative thrust, which facilitates aggressive trajectory tracking. However, the control allocation in the actuator for generating the commanded thrust and torque is not a static, linear relation, but is nonlinear and dynamic. Further, transient disturbances are present due to rapid variations in aerodynamic load on the rotor dynamics while varying the blade pitch angle. The proposed control law consists of a robust attitude controller augmented with a saturated thrust-feedback position controller. The control law is shown to almost-globally stabilize the tracking errors on SE(3) at an exponential rate. Numerical simulations on a model of a variable pitch quadrotor have been presented.

Keywords: Autonomous robotic systems, Guidance navigation and control, Perception and sensing
Abstract: This paper presents an algorithm to perform autonomous exploration with robotic platforms equipped with a stereo-vision system in indoor, unknown and cluttered environments. The accuracy of the vision-based localization depends on the quantity of visible features in the scene captured by the cameras. A Model Predictive Control approach permits to perform the exploration task with obstacle avoidance and taking into account the quality of the scene in order to avoid areas where the visual odometry is likely to fail. Experiments were carried out with a mobile robot to assess the improvement in localization accuracy and coverage for exploration.

Keywords: Flying robots, Guidance navigation and control, Autonomous robotic systems
Abstract: The aim of the SkyScanner project is to collect data in and around cumulus clouds to improve the modeling of meteorological phenomena. This work presents a finite time tracking control law for a small Unmanned Aerial Vehicle (UAV) in use within the project. The longitudinal dynamics of the UAV are considered and additive disturbances are added on the control inputs. The intention is to track the UAV pitch angle and the velocity with respect to the ground. An unusual representation of the model has been chosen considering the components of the wind velocity as additive inputs of the model. The control law is designed in two steps: firstly the system is input/output linearized with respect to the variables of interest, then a finite time control law is designed to track a reference signal and reject the injected disturbances. With input-output (I/O) linearization process a zero-dynamics problem arises and is studied. The results are formally proven and supported by simulations.

Keywords: Flying robots, Robots manipulators, field robotics
Abstract: The aim of this article is to establish a geometric, pulling force control scheme in order to enable the concept of Aerial Robotic Workers (ARWs), where the capabilities of the Unmanned Aerial Vehicles (UAVs) are enhanced by aerial manipulators in order to exert known pulling forces on the environment, with characteristic applications such as levers actuation, debris removal and safety assessments. The proposed novel approach consists of interfacing a cascaded position control scheme with a manipulation framework in such a way that the UAV, together with the manipulator, are being controlled in a complete system. The validity of the proposed scheme as well as the ability of the UAV to track a desired pulling force is validated through a real-world experiment.

Keywords: Flying robots, Guidance navigation and control
Abstract: Lightweight Unmanned Aerial Vehicles (UAV) are usually very sensitive to the external disturbances during outdoor experimentations. These adverse conditions make both the dynamic modeling and the control tasks more complex. Thus, it is necessary to employ an efficient control technique with acceptable performance without a complete knowledge of the disturbed model. This is because, in the classic feedback linearization control, the deviations between the model and the real plant may produce poor performance. Throughout the present paper, Dynamic Sliding Mode Control (DSMC) technique is designed to deal with the disturbances and which has never been used for quadrotors. Unlike the existing sliding mode techniques, the designed one uses an input-dependent sliding surface in order to enhance the robustness level of the classical feedback linearization control law. The effectiveness of this approach that ensures 3D trajectory tracking of quadrotor is demonstrated through numerical simulations.

Keywords: Flying robots, Autonomous robotic systems, Robotics technology
Abstract: Aerial transportation is probably the most efficient way to supply quick and effective aid especially in cases of emergency like search and rescue operations. Thus the ability to grasp and deliver objects is of vital importance in all sorts of unmanned and autonomous aerial operations. We detail a simple yet novel approach for aerial grasping of ferrous objects using a passive magnetic pickup and an impulse based drop mechanism. The design enables our gripper to grasp ferrous objects using single as well as multiple gripping pads, with visual as well as pickup and drop feedback. We describe the various components of the gripper with emphasis on its low mass and high lift capability, since weight is a matter of high consideration in all aerial applications. In addition, we investigate and address the issues that may cause our design to fail. We demonstrate by experiments that the proposed design is robust and effective, based on its high payload capability, its sturdiness against possible slide during aggressive aerial maneuvers, and optimum performance of the drop mechanism for the designed range of payloads. We also show that the gripper is able to pick up and drop a single as well as multiple ferrous objects of different shapes, curvature, and inclination, which also involves picking up an object and then grasping the next, while keeping hold of the previous one.

Keywords: Flying robots, Mobile robots, Motion Control Systems
Abstract: This paper studies the 3D trajectory tracking for the quadrotor commercial prototype AR.Drone 2.0 of the French company Parrot. The proposed control strategy is designed using a time-varying version of the backstepping technique. For the implementation of the control law, it is assumed that only the position and orientation of the AR.Drone are known; linear and angular velocities of the AR.Drone are estimated using suitable Luenberger observers. The proposed control strategy allows an AR.Drone 2.0 to converge asymptotically to a predetermined flight trajectory. The theoretical results are validated through real-time experiments.

Keywords: Flying robots, Identification and control methods
Abstract: It is well known in the literature on multirotor UAVs that the flight control performance is affected when operating close to the ground surface. While ground effect has been studied extensively for full scale helicopters, its study for multirotors has so far received limited attention. In particular, following an experimental investigation of static ground effect for a quadrotor platform, in this paper the problem of characterising the dynamic operation of the same platform in ground effect is considered and the results obtained in an experimental campaign to this purpose are presented and discussed.

Keywords: Intelligent interfaces, Human operator support, Perception and sensing
Abstract: This study shows the investigation of three dimensional (3D) reconstruction using a towing camera system in order to collect the information inside the nuclear plant for reactor decommissioning. The towing camera obtains time-series inside the nuclear plant by moving through a cable. The camera can move by pulling the cable. However, in this case, passive rotation affects the 3D reconstruction. In this study, in order to investigate effect of the passive rotation, the experiments are carried out for 3D reconstruction with actual camera at a mockup. In order to investigate influence of passive rotation, we prepare two types of camera. One is towing passive joint camera which is influenced by passive rotations and the other is towing fix joint camera which is not influenced by them. We compare 3D reconstruction from time-series images by these two cameras. A square log is adopted as a target for 3D reconstruction in mockup. Experimental results show that time-series images by a passive joint camera reconstruct the target more accurate and the floor more flatly in comparison to a fixed joint camera. Additionally, we verify that it is difficult to reconstruct the points with respect to the vertical height when towing camera is set to downward.

Keywords: Perception and sensing, Multi sensor systems
Abstract: The reduced cost of cameras and the complex scenes make it possible and necessary to replace the monocular camera with camera array under certain situations. In this paper, we first provide a review on the existing camera arrays and sort them according to the array arrangement, and then give an overview of the imaging properties that are benefited from the camera array including dynamic range, resolution, seeing through occlusions and depth estimation. At last, a novel camera array-based airborne optical system is proposed to meet the intelligence, surveillance and reconnaissance (ISR) requirements for large eld of view (FOV), high dynamic range and resolution, multi-view and multiple dimensions imaging. For the sake of onboard application of this system in practice, some key technologies were highlighted that need to be developed in the future research, such as the self-calibration and the synthetic aperture imaging by camera arrays on mobile platforms.

Keywords: Autonomous robotic systems, Identification and control methods, Design methodologies
Abstract: Many distributed systems rely on communication as a necessary condition to steer the overall system to a reference or target state, which may lead to a large bandwidth requirements. Here, we consider a Distributed Model Predictive Control Scheme (DMPC) where each agent predicts its own trajectory in every time step, which is then broadcasted among the agents. We aim to reduce the necessary communication and introduce the concept of prediction coherence as a degree of difference of two predictions in two successive time steps. We evaluate the influence of quantisation of communicated predicted states on the prediction coherence in a street traffic model for a quantised intersection in order to incorporate possible disturbances in communication. We numerically observe that prediction coherence reveals a bound for the minimal bandwidth requirements for such a distributed control setting.

Keywords: Decentralized control
Abstract: This paper deals with the problem of string stability of interconnected systems with double-integrator open loop dynamics (e.g. acceleration-controlled vehicles). We analyze an asymmetric bidirectional linear controller, where each vehicle is coupled solely to its immediate predecessor and to its immediate follower with different gains in these two directions. We show that in this setting, unlike with unidirectional or symmetric bidirectional controllers, string stability can be recovered when disturbances act only on a small (N-independent) set of leading vehicles. This improves existing results from the literature with this assumption. We also indicate that string stability with respect to arbitrarily distributed disturbances cannot be achieved with this controller.

Keywords: Fault-tolerant, Networked systems, Decentralized control
Abstract: This paper addresses the problem of fault-tolerant control in large-scale systems wherein the subsystems have to assure together a steady state control goal. It is considered that the faulty subsystem cannot be reconfigured locally and consequently, as a fault occurs, the command inputs of the fault-free systems have to be modified in order to guarantee the original control goal in the presence of fault as well. The proposed control strategy estimates the fault-induced modifications in the output of the faulty subsystem and, based on this information, recomputes the command inputs of the fault-free systems. To compensate the effect of the fault propagation through the physical interconnections, the local controllers of the subsystems are augmented with an external integral control loop. The stability and the networked implementation of the reconfiguration strategy are also treated. Simulation results are provided to show the applicability of the proposed fault-tolerant control strategy.

Keywords: Fault-tolerant, Adaptive control, Tracking
Abstract: In this paper, a novel actuator failure compensation scheme is proposed for affine nonlinear uncertain systems subject to actuator faults/failures unknown in time, magnitude and pattern. The proposed control methodology utilizes a backstepping procedure integrated with multiple estimation models to estimate failure induced parametric uncertainties and unknown system parameters. Relative to existing direct adaptive backstepping based fault compensation strategies in literature, the proposed actuator fault tolerant control (FTC) method yields a faithful accommodation of uncertain actuator failures while ensuring satisfactory output transient and steady state performances. Further, compared to multiple model based adaptive FTC design, the proposed methodology circumvents the issues of stability due to switching between different models and utilizes a minimum number of estimation models for parameter estimation without sacrificing the output performance and thereby reducing the computational burden. Simulation results illustrate the efficacy and applicability of the proposed method to FTC design problem for longitudinal pitch control of Boeing 747-100/200 aircraft.

Keywords: Decentralized control, Systems with time-delays, Disturbance rejection (linear case)
Abstract: In this paper, we consider the distributed consensus problem for multi-agent systems with input delay and unknown disturbances. To deal with the input delay and disturbances, a predictor- and disturbance observer-based control strategy is developed for each follower. Then, a distributed robust adaptive consensus protocol with dynamic coupling gains is proposed based on the relative state of the neighbouring agents, guaranteeing that all signals in the closed-loop dynamics are uniformly ultimately bounded and the consensus tracking error converges to an arbitrarily small residual set. The controllers are proposed in a fully distributed way such that the global information related to the eigenvalues of the Laplacian matrix is not needed. Finally, the validity of the proposed controller is demonstrated through a numerical example.

Keywords: Fault-tolerant, Switching control, UAVs
Abstract: This paper addresses the problem of loss of motor effectiveness for a quadrotor Unmanned Aerial Vehicle (UAV). In this paper, faults consist of time-varying actuator gain reductions. In the case of a fault affecting one actuator only, we show that the stability and the performance of the controlled system is maintained despite the fact that there is no fault detection mechanism involved in the design. The fault tolerant controller comprises of state feedback gains and a min-switch strategy which are jointly designed. Simulation results show that the switched fault tolerant control enables the quadrotor to track well the desired velocity commands in the presence of a time-varying fault. The responses are also compared to those produced with a robust H2 state-feedback gain.

Keywords: Fault-tolerant, Switching stability and control, Linear systems
Abstract: On the basis of fault-tolerant control theory and switching L2 gain analysis, we propose a new maintenance support technology to implement an operating state suitable for safely performing preventive maintenance of each subsystem, where the safety of the bidirectional transitions between normal operation and an operating state is guaranteed.

Keywords: Switching stability and control, Tracking, Robust control
Abstract: This work deals with the design method of robust switched H_inftyPI observer-based control for switched uncertain systems with external disturbances. All sufficient conditions for the robust stability of the closed-loop systems are established by using switched Lyapunov function and LMI/LME framework. Its performances are demonstrated through the vehicle dynamics application to estimate simultaneously lateral speed and road bank angle (unknown input) based on steering vehicle control. Simulations are performed using real data previously recorded by an instrumented vehicle.

Keywords: Decentralized control
Abstract: In this paper, we present a framework of evolutionary game theory and multi-agent systems to investigate how and why inactive "lazy" workers can enhance the group performance when doing circle formation tasks. Inspired by biological observations, the property of inactivity is introduced to the agents and qualified as their strategies in the proposed evolutionary framework, while the payoff of each agent relies on its energy consumption. We obtain that the system with lazy workers always evolves to a high level of inactive. We further analyze through simulations the relationship between inactive workers and the group performance. It is shown that the decentralized multi-agent system with the property of inactivity can improve its group performance by means of the evolution of the agents' inactivities.

Keywords: Controller constraints and structure, Decentralized control, Output feedback control (linear case)
Abstract: This paper addresses the design of sparse, mathcal{H}_2-optimized dynamic output feedback controllers for distributed systems. These systems consist of several physically remote subsystems, which are assumed to be controlled via local controllers. Depending on the topology of a communication network, subsets of these controllers may exchange information. In this setting, a trade-off between control performance and communication costs exists: while a network which connects more controllers increases control performance, establishing communication links also causes higher costs. In the past, the Alternating Direction Method of Multipliers (ADMM) has been applied to the design of state feedback controllers that optimize this trade-off. Due to the practical relevance of output feedback, this paper provides extensions necessary for application of the ADMM to the output feedback case. Motivated by deeper insights into the non-convex, non-smooth nature of the problem, the HANSO optimization package is applied to the controller performance optimization subproblem of the ADMM. The devised procedure is successfully applied to two example systems.

Keywords: Controller constraints and structure, Systems with time-delays, Linear systems
Abstract: The sparse memoryless LQR design problem is formulated for uncertain linear time-delay systems. In such a problem, the goal is to minimize a quadratic cost supplemented by sparsity-promoting term (weighted-ell_1 in our case) subject to stability of closed-loop system under norm-bounded uncertainty. It is shown that such an optimization problem can be reformulated as a rank-constrained optimization problem which consists of convex constraints except one rank constraint. Utilizing the bi-linear rank penalty technique, the sparse memoryless LQR is designed. Numerous numerical results depict that there exists a trade-off between time-delay and sparsification quality. In addition, the larger time-delay, the poorer performance-sparsity trade-off is observed.

Keywords: Switching stability and control, Control of switched systems, Power systems
Abstract: In this paper, we consider a class of switched affine systems encountered in many applications and in particular in DC-DC power converters. We propose a switched and adaptive control design methodology with a global asymptotic stability property. The proposed control strategy is based on a joint observer and parameter estimation. As an application, we focus in this paper on the case of Flyback converters and the main contribution is to prove that this switched and adaptive control strategy provides a stability guarantee in both continuous and discontinuous conduction modes.

Keywords: Data-based control
Abstract: This paper presents an error-entropy minimization tracking control algorithm for a class of dynamic stochastic system. The system is represented by a set of time-varying discrete nonlinear equations with non-Gaussian stochastic input, where the statistical properties of stochastic input are unknown. By using Parzen windowing with Gaussian kernel to estimate the probability densities of errors, recursive algorithms are then proposed to design the controller such that the tracking error can be minimized. The performance of the error-entropy minimization criterion is compared with the mean-square-error minimization in the simulation results.

Keywords: Data-based control, Linear systems
Abstract: This paper presents a data driven approach for PI control design based on frequency response data and calculations of stabilizing sets. The geometrical interpretation of the loci of stability margins allows to determine the parameters of a PI controller from a space of achievable specifications, constructed from frequency response data. As illustration for the use of the proposed approach in engineering applications, regulation of the output voltage of a boost power converter circuit under a double loop control strategy is presented. Numerically, it was possible to generate enough amount of data to perform accurate predictions. The key to apply the proposed approach with success was the generation of a Bode diagram for the system with fine resolution, avoiding the explicit necessity for mathematical models.

Keywords: Adaptive control, Decentralized control, Quantized control
Abstract: In this paper, a decentralized adaptive control scheme is proposed for a class of uncertain nonlinear interconnected systems with input quantization. A hysteresis uniform quantization is introduced to reduce chattering. In the control design, a smooth function is introduced with backstepping technique to compensate for the effects of interactions. It is shown that the proposed decentralized adaptive controllers can ensure global boundedness of all the signals in the closed-loop interconnected systems and the tracking errors of subsystem converge to a residual, which can be adjusted by choosing suitable design parameters. Simulation results illustrate the effectiveness of the proposed control scheme.

Keywords: Adaptive control, Output regulation, Quantized control
Abstract: This paper proposes a new adaptive controller for uncertain nonlinear systems in presence of quantized input signal and unknown external disturbance. A hysteresis quantizer is incorporated to reduce chattering phenomenon. By proposing a new transformation of the final control signal, using the sector-bound property of the quantizer and introducing a hyperbolic tangent function, the effects from input quantization and external disturbance are effectively compensated and the Lipschitz condition required for the nonlinear functions in the systems is removed. Besides showing global stability, tracking error performance is also established and can be adjusted by tuning certain design parameters. A numerical example is presented to demonstrate the effectiveness of the proposed adaptive control scheme.

Keywords: Adaptive control, Time-varying systems, Fractional systems
Abstract: This paper deals with model-based fractional order controller design. The objective is identification for controller design in order to achieve the desired closed-loop performances. Firstly, the fractional order closed-loop bias-eliminated least squares method is used to identify the process model. Then, based on the numerical optimization of a frequency-domain criterion, the fractional controller is designed. If the proposed algorithm detects any changes in the process parameters, the controller is updated to keep the same performances. A numerical example is presented to show the efficiency of the proposed scheme.

Keywords: Data-based control, Robust control (linear case), Convex optimization
Abstract: A novel method to design data-driven, fixed-structure controllers with H₂ and H_∞ performance objectives is presented. The control design problem is transformed into a convex optimization problem with linear matrix inequality constraints, which can be solved efficiently with standard solvers. The method is used to design a data-driven controller for an atomic-force microscope. The closed-loop performance of the calculated controller is validated on a real setup.

Keywords: Control in system biology, Asymptotic stabilization, Fractional systems
Abstract: In this paper, a fractional genetic regulatory network with diffusion is proposed and several dynamic behaviors are investigated. The local stability and instability without and with diffusion are studied, respectively. The criteria for the instability with diffusion are obtained on the biological parameter and spatial parameter. Numerical simulations are given to illustrate the theoretical results and also show the effect of the fractional order on the stability and oscillations. Spatially inhomogeneous steady states which do not arise in corresponding integral-order diffusive model are found.

Keywords: Controller constraints and structure, Static optimization problems, Convex optimization
Abstract: This paper considers Iterative Convex Overbounding (ICO) techniques for Bilinear Matrix Inequality (BMI) problems. It is very common for BMIs to be present in multi-objective control, as well as many other optimization problems. Theoretically, ICO techniques guarantee monotonic convergence to a local optimum, and do not require the introduction of conservatism or relaxations. In this work, we propose an update to ICO which allows for improved results and a new convergence path. We also illustrate that ICO techniques are extensible to problems in which initial feasible design points are not known. Finally, we illustrate that ICO can be extended to matrix polynomial inequalities of arbitrary finite order. These ideas are demonstrated on a simple example.

Keywords: Model validation, Application of nonlinear analysis and design, Modeling for control optimization
Abstract: This paper presents a more accurate model of a Furuta double pendulum for efficient planning of optimal trajectories using the new approach of discrete mechanics and optimal control (DMOC). Based on the variation of discrete mechanics a direct discretization of the Lagrange-d'Alembert principle enables a novel formulation of the optimization problem. This leads to less optimization parameters and thus more computational efficiency. To shed the light on the advantages of the proposed method the swing-up maneuver of the Furuta double pendulum is used to demonstrate the point-to-point trajectory planning. For this purpose, a model of Furuta double pendulum based on Denavit-Hartenberg convention with higher accuracy is presented additionally.

Keywords: Parametric optimization, Lyapunov methods, Stability of nonlinear systems
Abstract: In this paper, we consider the problem of synthesizing static output feedback controllers for stabilizing polynomial systems. We jointly synthesize a Lyapunov function and a static output feedback controller that stabilizes the system over a given subset of the state-space. Motivated by the numerical issues that are commonly faced using SOS (Sum Of Squares)/SDP (semi definite programming) solvers, we examine a linear programming (LP) based alternative approach that can yield more precise results, in practice. Our approach uses Bernstein polynomials to relax parametric polynomial optimization problems into bilinear optimization problems (BP). Subsequently, we approach the bilinear inequalities using a modified co-ordinate descent approach that alternates between solving linear programs on complementary sets of variables. Finally, we provide a comparison between our approach and BMI (Bilinear matrix inequalities) solvers that tackle the same problem. We conclude that LP/BP relaxation approach is promising and can be more efficient than SDP/BMI relaxations.

Keywords: Parametric optimization, Convex optimization, Large scale optimization problems
Abstract: We present an approximation method to a class of parametric integration problems that naturally appear when solving the dual of the maximum entropy estimation problem. Our method builds up on a recent generalization of Gauss quadratures via an infinite-dimensional linear program, and utilizes a convex clustering algorithm to compute an approximate solution which requires reduced computational effort. It shows to be particularly appealing when looking at problems with unusual domains and in a multi-dimensional setting. As a proof of concept we apply our method to an example problem on the unit disc.

Keywords: Analytic design, Lyapunov methods, Asymptotic stabilization
Abstract: The paper focuses on the development of the navigation function approach for nonlinear systems with fast oscillating controls. This approach allows to solve the obstacle avoidance problem and generate reference trajectories on the state space with obstacles by using the gradient flow of a navigation function. In general, such gradient flow cannot be implemented for underactuated control systems, and an approximation of non-admissible velocities is needed for the control design. We present here an approximation result under low-order controllability assumptions. Our control design scheme is illustrated by an example of a nonholonomic system.

Keywords: Navigation, Guidance and Control, Guidance, navigation and control of vehicles, Robot Navigation, Programming and Vision
Abstract: In this article, we present a novel anti-windup method for vision based control. Technically speaking, this method aims at controlling a second order chain of integrators with the first component being known up to an unknown, time-varying scaling factor, and including control saturations. This complex problem is of pratical relevance since it appears naturally in the context of vision-based control, the position of an object being determined from bi-dimensional images, so that it is known up to a factor. Saturations are also obviously present in such a context. To address this issue, we combine a tailored observer together with an anti-windup scheme. Uniform global asymptotic stability of the closed loop system is proven. Finally, simulation results demonstrate the effectiveness of the method.

Keywords: Decision making and autonomy, sensor data fusion, Motion control, Guidance, navigation and control of vehicles
Abstract: While autonomous multirotor micro aerial vehicles (MAVs) are uniquely well suited for certain types of missions benefiting from stationary flight capabilities, their more widespread usage still faces many hurdles, due in particular to their limited range and the difficulty of fully automating the deployment and retrieval. In this paper we address these issues by solving the problem of the automated landing of a quadcopter %off the bed of a pickup truck on a ground vehicle moving at relatively high speed. We present our system architecture, including the structure of our Kalman filter for the estimation of the relative position and velocity between the quadcopter and the landing pad, as well as our controller design for the full rendezvous and landing maneuvers. The system is experimentally validated by successfully landing in multiple trials a commercial quadcopter on the roof of a car moving at speeds of up to 50 km/h.

Keywords: Guidance, navigation and control of vehicles, Control of systems in vehicles, Safety
Abstract: This paper uses a control strategy to visually control a helicopter, by combining Image-Based Visual Servoing (IBVS) and a Translational Rate Command (TRC) law. This strategy could initially be used to track a ship before landing, but it was possible only under restrictive conditions due to the machine limits. The goal is to take into account these constraints by adding a module based on filtering and anti-windup techniques between the IBVS and the TRC law. This module generates more realistic velocity commands to be followed and improves stability margins. Results show a good applicability for ship tracking. Models include helicopter and ship dynamics, actuators, and embedded camera.

Keywords: Navigation, Guidance and Control, Autonomous Vehicles
Abstract: Autonomous landing is the most difficult maneuver in a quadrotor mission because of challenges like (i) external disturbances causing deviation from the desired trajectory resulting in a crash and (ii) inaccuracy of GPS based landing due to localization errors. In this paper, we use onboard vision to detect and estimate the landing pad coordinates accurately. We develop a novel closing velocity controller and integrate it with pure pursuit guidance law to achieve faster and accurate landing in 3D as compared to traditional vertical landing approaches. We test the efficacy of the proposed controller for stationary and moving landing pad through simulations and validate the controller through outdoor experiments for a stationary landing pad.

Keywords: Guidance, navigation and control of vehicles, Autonomous systems, Robot Navigation, Programming and Vision
Abstract: A vision-based control law has been developed and applied to a helicopter landing on a moving ship at sea. A compensation of the ship platform motion due to the waves has been provided as well, obtained through an estimation of the platform velocity. The outer, vision-based control loop is feeding an inner control loop for the stabilization through pole placement of the helicopter naturally unstable flight dynamics modes. Simulation results show good performances of the overall control loop, with an efficient compensation of the perturbations due to the ship deck motion.

Keywords: Guidance, navigation and control of vehicles
Abstract: Unlike standard landing control laws, vision-based systems exploit specific measurements which, as shown in this paper, introduce a rapidly growing parameter in the closed-loop system to be evaluated. Moreover, during the landing phase, high gains are often used to ensure performance despite perturbations. As a result, saturations are likely to appear. Based on parameter-dependent Lyapunov functions, an efficient algorithm is proposed in this paper to characterize stability and performance of parameter-varying systems with control input saturations. The algorithm is then successfully applied to the evaluation process of a simple vision-based landing system.

Keywords: Digital enterprise, Systems interoperability, Interoperability requirements
Abstract: This article focuses on the relevance of a digital approach as BIM in the particularly dynamic and diversified renovation sector, mainly driven by micro enterprises (μEnt). The state of the art shows that few scientific references are devoted to this subject and that the technologies and tools available, which are often very costly, have not demonstrated their profitability (and feasibility) for this business typology. An extensive literature review is used to define the scope and terms of the field of renovation. It demonstrates the areas of interest for a BIM approach and highlights some gaps that should be filled with future works. It is necessary to better map the different observable renovation processes, as well as adapt or develop an appropriate BIM maturity measurement tool for this renovation sector and for μEnt.

Keywords: Enterprise modelling and BPM, Model-driven systems engineering
Abstract: This paper presents how Functional Programming (FP) helps to provide an other formal semantics (relation between the syntax and the model of computation) for Business Process Modeling (BPM); a semantics relatively different from Object Oriented semantics. More precisely, it proposes a general methodology to model business processes using mathematical functions and higher-order functions. We describe the basic part of Business Process Modeling, behavioral semantics via Petri Nets (PN) and Functional implementation of the models. Also, we will see how the business process model is translated into its equivalent form in Petri Nets and how these can be described through Functional Programming.

Keywords: Collaborative networked organizations principles, Enterprise networks design and implementation
Abstract: Sharing resources could be an interesting and strategic choice for enterprises owing to their benefits. If the benefit of renting or trading are the forms of sharing that may affect enterprises of different sizes, the joint purchase and joint use can be a form of sharing interesting for SMEs which may have difficulties to buy individually production resources. However, this production resource sharing may induce possible cheatings by one of the SMEs. These cheatings, commonly deviations from the initial share’s contract, are disadvantageous for the other company. The study of these possible deviations and the level of investment held by the company for the detection of deviations are then necessary. That’s why, we propose in this paper to model the production resource sharing between two small enterprises and possible cheatings to evaluate them and their impact on the collaboration. The chosen model is a non-cooperative game since it allows individual profits description. Then, we compare the strategies of the game and all possible cases of cheating for each SME on the horizon of the game.

Keywords: Model-driven systems engineering, Modelling and control of hybrid and discrete event systems
Abstract: Model-Based System engineering (MBSE) promotes Verification and Validation (V&V) as crucial activities to demonstrate, during the system design stage and based on models, that a system meets requirements defined by stakeholders and that it fulfills its intended purpose. Model V&V activities are defined through the following strategies: Model Appraisal, Guided Modelling, Simulation and Formal Proof. Regarding the objectives of each individual strategy, they are considered as complementary, therefore mutually beneficial when combined, for reaching the overall V&V objectives. Various techniques and tools permit nowadays the implementation of each strategy. However, the successful combination and implementation of all four strategies remains still difficult (difference of concepts), time consuming (transformation and dedicated modelling are often requested) and generally expensive. This paper introduces a tool-equipped method for the successful and eased combination and implementation of all four V&V strategies to provide stakeholders with a high level of confidence in decision-making based on models.

Keywords: Collaborative networked organizations principles, Enterprise networks design and implementation, Business process management systems
Abstract: Due markets turmoil, the development of tools that allow risk analysis in organizations is increasingly critical in order to ensure the survival of organizations. Depending on the type of risk to be identified, it is necessary to use appropriate techniques that allow a diagnosis as concrete as possible, to timely detect risks and thus develop management policies that minimize their impact. In this paper is discussed how through the application of social network theory is possible to identify and quantify existing or potential hazards for example at the level of communication, management and sharing of knowledge among several actors of an organization in a collaborative context.

Keywords: Decentralized and distributed control, Optimization and control of large-scale network systems, Multiagent systems
Abstract: In this paper, the problem of power allocation is considered for distributed estimation over a sensor network with limited power. An online power allocation scheme is introduced to optimize the power consumption, where the power distributed to each communication channel depends on the innovation value of the transmitter. First, an optimal estimator gain is designed for each sensor by minimizing the mean-squared estimation error covariance. Second, a sufficient condition is provided to guarantee the stability of networked system with online power allocation scheme. Finally, we compare the estimation performance of the proposed online power scheduling scheme with some typical offline power scheduling schemes.

Keywords: Bayesian methods, Nonparametric methods
Abstract: We study the problem of identifying dynamic networks that do not present loops. We model the impulse responses of the modules in the network as zero-mean independent Gaussian processes. The covariance matrices of the processes can be used to encode prior information, such as stability and smoothness, about the impulse responses of the modules. To estimate the modules, we approximate the joint posterior distribution of the impulse responses using a variational Bayes approach. In particular, using a mean-field approximation, we assume a factorization of the posterior where each factor corresponds to a single module. We estimate the kernel hyperparameters and the measurement noise variances by combining variational Bayes with the expectation-maximization method. We evaluate the performance of the identification procedure in a simulation experiment, where we compare to other kernel-based approaches.

Keywords: Closed loop identification, Multi-agent systems
Abstract: In dynamic network identification usually the assumption is made that there is a full rank process noise affecting the network. For large scale networks with many variables this assumption is not realistic as the noise could be generated by a limited number of sources. We extend prediction error identification methods by allowing rank-reduced process noise in the network. The developed method is based on a modification of the typical predictor expression and an appropriate modification of the identification criterion. It is shown that this method leads to consistent estimates, and we provide a method to reduce the variance of the estimates, which is confirmed by simulations.

Keywords: Closed loop identification, Nonparametric methods, Errors in variables identification
Abstract: For identification of systems in dynamic networks, two-stage and instrumental variable methods are common time-domain methods. These methods provide consistent estimates of a chosen module of the network without estimating other parts of the network or noise models. However, disregarding noise modeling may come at a cost in estimation error. To capture the noise contribution, we propose the following procedure: first, we estimate a non-parametric model of an appropriate part of the network; second, we estimate the module of interest using signals simulated with the non-parametric model. The simulated signals are derived from an asymptotic maximum likelihood criterion. Preliminary simulations suggest that the propose method is competitive with existing approaches and is particularly beneficial with colored noise.

Keywords: Errors in variables identification, Closed loop identification
Abstract: The interest for system identification in dynamic networks has increased recently with a wide variety of applications. In many cases, it is intractable or undesirable to observe all nodes in a network and thus, to estimate the complete dynamics. Furthermore, it might even be challenging to estimate a subset of the network if key nodes are unobservable due to correlation between the nodes. In this contribution, we will discuss an approach to treat this problem. The approach relies on additional measurements that are dependent on the unobservable nodes and thus indirectly contain information about them. These measurements are used to form an alternative indirect model that is only dependent on observed nodes. The purpose of estimating this indirect model can be either to recover information about modules in the original network or to make accurate predictions of variables in the network. Examples are provided for both recovery of the original modules and prediction of nodes.

Keywords: Input and excitation design, Time series modelling
Abstract: The identification of networks from measured data has been studied for many years in computer science and statistics. Central to this topic is the identifiability of the network, also called reconstructibility or faithfulness in these communities. This paper examines a class of networks in which the node signals, assumed measurable, are connected by linear time-invariant transfer functions, and in which a noise signal and/or a known excitation signal may or may not be present at each node. The paper discusses the notion of network identifiability. It then proposes a definition that is shown to be efficient for the reconstruction of a dynamical network from measured data. This allows us to exhibit a parametrization of all equivalent network models that are consistent with the data, and thereby to produce a range of sufficient conditions for network identifiability. These conditions (in the form of prior knowledge on the structure of the excitations) show that for the identification of a dynamical network a trade-off exists between excitation from known external signals and excitation from the noise.

Keywords: Time series modelling, Closed loop identification, Stochastic system identification
Abstract: This paper addresses reconstruction of linear dynamic networks from heterogeneous datasets. Those datasets consist of measurements from linear dynamical systems in multiple experiments subjected to different experimental conditions, e.g., changes/perturbations in parameters, disturbance or noise. A main assumption is that the Boolean structures of the underlying networks are the same in all experiments. The ARMAX model is adopted to parameterize the general linear dynamic network representation "Dynamical Structure Function" (DSF), which provides the Granger Causality graph as a special case. The network identification is performed by integrating all available datasets and promote group sparsity to assure both network sparsity and the consistency of Boolean structures over datasets. In terms of solving the problem, a treatment by the iterative reweighted l₁ method is used, together with its implementations via proximal methods and ADMM for large-dimensional networks.

Keywords: Ethics, Conflict and Post-conflict, Technology Transfer
Abstract: The paper considers a number of important questions related to the involvement of engineers in peacebuilding and military work, including the preference of many countries for high tech weapons based security over peacebuilding, whether and in what circumstances, if any, it is justified for engineers to be involved in military work; and how engineers can persuade their colleagues to apply their skills to support peacebuilding. It is introduced by an overview of what is meant by the term military work and the extent and consequences of the use of military technology worldwide. This is followed by the applications of different approaches and theories of ethics to discuss the questions presented in the introduction. The approaches and theories applied include considerations of micro-and macro-ethics, codes of ethics, virtue ethics, considerations of gender and paradigms and the ethical imperative. Initial insights include the importance of considering the associated context and the need to avoid othering, which can make different treatment of minority groups, including the use of high tech weapons against them, seem acceptable.

Keywords: Ethical challenges and issues in social networking
Abstract: Implementing Digital Data Gathering methods and other ICT approaches are now an integral part of work in international development, with most involved organisations utilising them in a variety of different and innovate ways. Such approaches have had very significant benefits to implementing organisations, and participants and stakeholders on such projects and programmes. This paper examines some of the challenges that utilising these technologies raise that have yet to be overcome, with particular regard to obtaining informed consent, the meaning of that consent, and data sharing.

Keywords: Policy, International Development, Knowledge Society
Abstract: Since IFAC was established in the post-world war two cold war context, the international system has changed in very fundamental ways. However, IFAC retains a strong and active membership, not least in Technical Committee 9-5 which deals with IFACs scientific engagement with the international system. What do IFAC members think about this engagement? This paper reviews the results of data gathered IFAC meetings which explored member perspectives on global stability challenges and system features. The findings synthesise the views and priorities across various groups, including younger and older members. The paper proposes concrete IFAC priorities arising from this data for future engagement across the control and automation community and with external agencies with a view to contributing to the IFAC international engagement agenda. It forms the basis for a wider discussion about IFAC aspirations and actions, especially in CC9 and TC 9-5.

Keywords: Ethics, Modelling Social and Environmental Change, Multi-cultural interaction
Abstract: Engineers have a very important role and responsibility in shaping modern society. Diversity amongst engineers is important in fulfilling this responsibility and ensuring that the creativity and needs of the whole population are taken account of. However, only a small percentage of engineers are female and very few of them are disabled. The paper discusses the experiences of women and disabled engineers in the context of othering and considers the way in which the existence of binary divides facilitates marginalisation and exclusion. It also discusses the need to involve end-users in design and development and education to encourage this, with a particular focus on disabled end-users.

Keywords: Control problems under conflict and/or uncertainties, Uncertainty descriptions, Nonlinear predictive control
Abstract: Simulation studies of oil field water flooding have demonstrated a significant potential of optimal control technology to improve industrial practices. However, real-life applications are challenged by unknown geological factors that make reservoir models highly uncertain. To minimize the associated financial risks, the oil literature has used ensemble- based methods to manipulate the net present value (NPV) distribution by optimizing sample estimated risk measures. In general, such methods successfully reduce overall risk. However, as this paper demonstrates, ensemble-based control strategies may result in individual profit outcomes that perform worse than real-life dominating strategies. This poses significant financial risks to oil companies whose main concern is to avoid unacceptable low profits. To remedy this, this paper proposes offset risk mimimization. Unlike existing methodology, the offset method uses the NPV offset distribution to minimize risk relative to a competing reference strategy. Open-loop simulations of a 3D two-phase synthetic reservoir demonstrate the potential of offset risk minimization to significantly improve the worst case profit offset relative to real- life best practices. The results suggest that it may be more relevant to consider the NPV offset distribution than the NPV distribution when minimizing risk in production optimization.

Keywords: Real-time control, Decentralized control
Abstract: We present a framework for distributed, energy efficient, and real time implementable algorithms for path planning in multi-agent systems. The proposed framework is presented in the context of a motivating example of capture the flag which is an adversarial game played between two teams of autonomous agents called defenders and attackers. We start with the centralized formulation of the problem as a linear program because of its computational efficiency. Then we present an approximation framework in which each agent solves a local version of the centralized linear program using only its own information and the information of its immediate neighbors. The premise in this work is that for practical multi-agent systems, real time implementability of distributed algorithms is more crucial then global optimality. Thus, in this work, instead of verifying the proposed framework by performing offline simulations in MATLAB with oversimplifying assumptions on agents dynamics, we implement it on an actual multi-agent system comprising of three quadrotors in a lab environment. We also run extensive simulations in a robotic simulator V-REP that offers a more practical model of quadrotors. Moreover, to make simulations more realistic, we allow humans to control the attacker quadrotor through a joystick in a single attacker scenario to remove any simplification that can arise due to assumed attacker model in the simulations. Through hardware implementation and realistic simulations in V-REP, we confirm that the proposed framework is real time implementable and results in a performance that is comparable with the global optimal solution under the considered scenarios.

Keywords: Real-time control, Industrial applications of optimal control, Control of constrained systems
Abstract: Model predictive control applications have broadened from industrial plants with slow system dynamics to the implementation of trajectory planning and control algorithm on low-cost hardware. Ip2go has been developed with the aim of making model predictive control readily accessible on embedded systems. It generates efficient, problem-tailored solvers for optimal control problems. The code generator implements Mehrotra’s predictor-corrector interior-point method with Riccati recursion. It can be applied to quadratic programming problems, with linear discrete system dynamics and polytopic inequality and soft constraints. In this paper the features of ip2go, the underlying algorithm, the benefits of code generation and the generation process are set out. The comparison of ip2go-generated solvers to state-of-the-art solvers shows that ip2go can compete in terms of efficiency and code-size. The open and modular design allows all users to amend the generator. The Matlab based C-code generator ip2go is available under (https://github.com/fabiankrank/ip2go).

Keywords: Static optimization problems, Modeling for control optimization, Real-time control
Abstract: In a previous work an algorithm with linear-time computational complexity with respects to the number of variables is presented, providing an optimal solution for the minimum-time velocity planning problem. One limitation of such work is that the obtained velocity profile is not sufficiently smooth. In this work we try to obtain a smoother velocity profile, adding additional constraints on the absolute value of the second derivative of velocity with respect to the arc-length. We propose an algorithm that is able to efficiently solve the minimum-time velocity planning problem when only the lower bound of the second derivative of the velocity is considered. We will also see that the minimum time velocity planning problem under consideration belongs to a more general class of optimization problems, which can be tackled by the same approach. The approach is illustrated through an example and tested over a set of randomly generated instances. Properties of the proposed algorithm are proved.

Keywords: Industrial applications of optimal control, Optimal control theory
Abstract: We show how to minimize the energy required to build up the electromagnetic field in radio-frequency cavities, which will allow power savings for pulsed particle accelerators. By formulating an optimal control problem for a first-order system we obtain a solution on state-feedback form. We numerically compare the optimal solution to previous approaches.

Keywords: Optimal control theory
Abstract: Several studies have proposed different definitions of resilience during the past two decades. While reviews of part of the literature were published, a comparative analysis of the extant definitions is still lacking. This article critically analyzes the current definitions of resilience and show their limits and applicability domains especially in control theoretic situations. Further contributions of this article are the conversion of several qualitative definitions into quantitative ones and the determination of the level of compliancy of the discussed definitions with desirable properties, such as monotony in the variables.

Keywords: Constrained control, Application of nonlinear analysis and design, Sliding mode control
Abstract: This paper presents the Robust Generalized Dynamic Inversion (RGDI) control system for Autonomous Underwater Vehicles (AUV)s. The outer (position) and the inner (attitude) loops of the control system utilize Generalized Dynamic Inversion (GDI) of two pre-specified asymptotically stable dynamics of the inertial position coordinates and the attitude angles, respectively. The outer loop provides the pitch and yaw tilting commands to the inner loop, which in turns generates values of the corresponding control surface deflections by which the vehicle's position is controlled. Sliding mode control-based elements are included in the particular parts of the two GDI control loops, and they work to robustify the GDI control system against instabilities and performance deterioration due to unmodeled nonlinearities, parametric variations, and unknown bounded disturbances. A Lyapunov stability analysis of the proposed RGDI control law is presented, and a detailed six degrees of freedom mathematical model of the Monterey Bay Aquarium Research Institute AUV is used to evaluate the controller performance. Numerical simulations are conducted under both nominal and perturbed conditions to demonstrate robustness of the control design.

Keywords: Constrained control, Asymptotic stabilization, Lyapunov methods
Abstract: In this paper the regulation problem for continuous-time stochastic systems by linear state-feedback under state and/or control constraints is investigated. Nonlinear dynamical systems affected by stochastic disturbances modelled as q-dimensional Wiener processes with independent components are considered. Linear inequalities on the mean values of the state and the control are considered as control constraints. The analysis is based on the use of monotone comparison systems for Ito type stochastic differential equations and the positive invariance of polyhedral sets. This enables one to derive stability properties in terms of the convergence of the state vector mean values, thus avoiding complicated computations faced when stability properties are obtained by studying the behavior of higher order moments. For the class of linear systems a design approach based on linear programming is proposed.

Keywords: Constrained control, Optimal control theory, Controller constraints and structure
Abstract: This paper presents an algorithm for Model Predictive Control of SISO systems. Based on a quadratic objective in addition to (hard) input constraints it features soft upper as well as lower constraints on the output and an input rate-of-change penalty term. It keeps the deterministic and stochastic model parts separate. The controller is designed based on the deterministic model, while the Kalman filter results from the stochastic part. The controller is implemented as a primal-dual interior point (IP) method using Riccati recursion and the computational savings possible for SISO systems. In particular the computational complexity scales linearly with the control horizon. No warm-start strategies are considered. Numerical examples are included illustrating applications to Artificial Pancreas technology. We provide typical execution times for a single iteration of the IP algorithm and the number of iterations required for convergence in different situations.

Keywords: Control of constrained systems, Analytic design
Abstract: We consider the terminal control problem for affine dynamical systems that are differentially flat. Two different analytical approaches are proposed in the presence of state constraints. One is based on the parametric set of functions that satisfy an integral equation. The other one utilizes time polynomials that are monotonic on the relevant time intervals. As an illustrative example the motion of a 3-DoF Delta parallel robot is considered.

Keywords: Control of constrained systems, Constrained control, Robust control
Abstract: Robust output feedback control using model predictive control and observers is an important yet rather unexplored topic. This work proposes a controller that consists of a state estimator and a tube based robust predictive control law. In contrast to existing approaches, a single tube is used, which directly bounds the worst case difference between the real behavior and the predicted behavior. This allows to take the interaction between the estimation error and the error in the prediction better into account and leads to less conservative bounds. Conditions to guarantee robust constraint satisfaction and robust stability are presented. The results are illustrated by examples.

Keywords: Control of constrained systems, Constrained control, Systems with saturation
Abstract: In this paper, we show how time-scale transformations (TST) can be used for the control of nonlinear sytems subject to positive constraints. Such transformations, which consist in a change of the time variable, enable to define a new time-scale denoted τ in which the control problem becomes unconstrained and is therefore simplified. Classical methods such as dynamic feedback linearizing control design can then be used, leading to control laws that naturally fullfill the input positive constraints. The proposed method is applied on two concrete examples and compared with an other approach.

Keywords: Real-time control, Control of constrained systems, Controller constraints and structure
Abstract: This paper demonstrates an efficient approach for the implementation of parametric programming solutions to linear model predictive control problems. The emphasis is put namely on embedded hardware applications where feasible size and online evaluation of the controller code can be mission critical. As the explicit solutions are known to become quickly intractable for such a purpose once the amount of problem data grows, we exploit the concept of convex lifting of a given parameter space partition, and use it to avoid its storage and to replace the traditional point location with a significantly less costly procedure. In this light we practically illustrate the deployment of generated code on an 8-bit microcontroller unit, representing the class of low-cost embedded controllers built into mass-produced devices, in an active vibration suppression case study accompanied by a detailed performance, memory and timing analysis.

Keywords: Controller constraints and structure, Digital implementation, Analytic design
Abstract: This work presents a novel constraint handling strategy for Predictive Functional Control (PFC). First, to improve prediction consistency, the constant input assumption of nominal PFC approaches is replaced with Laguerre based prediction. This substitution improves the effectiveness of using a constrained solution to prevent long-term constraint violations. Secondly, for state constraints, a simpler single regulator approach is proposed instead of switching between regulators, an approach common in the PFC literature. Simulation results verify that the proposed method manages the constraints better than the traditional approach. Moreover, despite all the modifications, the controller formulation and framework remain simple and straightforward which thus are in line with the key ethos of PFC.

Keywords: Nonlinear predictive control, Time-varying systems
Abstract: Stability for economic Model Predictive Control (MPC) is in general difficult to establish. In contrast, tracking MPC has well-established stability guarantees, but can yield poor closed-loop performance in terms of the selected economic criterion. In Zanon et al. (2016a), a formal procedure to design a tracking MPC scheme so as to locally approximate the behaviour of economic MPC was proposed for the case of optimal steady-state operation. In this paper, we extend that result to the periodic case and provide a procedure to compute the tracking stage cost numerically. We illustrate our developments in a simulated example.

Keywords: Real-time control, Application of nonlinear analysis and design, Control of constrained systems
Abstract: This work presents a real-time implementable, computationally light algorithm for semi-active seat-belt systems. It consist of a linear feedback loop on the belt force that is cascaded by an algebraic reference governor. The governor is based on the explicit solution to a widely used optimization problem regarding optimal control of seat-belts. The algorithm is applied to a prototype semi-active hydraulic seat-belt actuator and is demonstrated on an experimental setup simulating frontal collisions. In comparison to an uncontrolled experiment, the controlled one managed to reduce the injury criterion with 15%, without increasing the occupant travel. When twice the travel was allowed, the criterion was reduced by 51%, showing the effect of variable settings to occupant/vehicle dimensions. However, the injury criteria were still 2:0 􀀀 2:5 times the optimal injury criterion, as calculated with perfect future knowledge of the crash.

Keywords: Control design for hybrid systems, Real-time control, Control of switched systems
Abstract: The execution of a hybrid model predictive controller (MPC) on an embedded platform requires solving a Mixed-Integer Quadratic Programming (MIQP) in real time. The MIQP problem is NP-hard, which poses a major challenge in an environment where computational and memory resources are limited. To address this issue, we propose the use of accelerated dual gradient projection (GPAD) to find both the exact and an approximate solution of the MIQP problem. In particular, an existing GPAD algorithm is specialized to solve the relaxed Quadratic Programming (QP) subproblems that arise in a Branch and Bound (B&B) method for solving the MIQP to optimality. Furthermore, we present an approach to find a suboptimal integer feasible solution of a MIQP problem without using B&B. The GPAD algorithm is very simple to code and requires only basic arithmetic operations which makes it well suited for an embedded implementation. The performance of the proposed approaches is comparable with the state of the art MIQP solvers for small-scale problems.

Keywords: Constrained control, Parametric optimization, Tracking
Abstract: The performance of a driving simulator depends on the efficiency of the embedded motion cueing algorithm. An explicit model predictive control was established recently as a pertinent design framework for the motion cueing algorithm. The complexity of the explicit solution increases manifold when the human vestibular model is considered. The present paper focuses on the complexity reduction of explicit solution using low complexity contractive sets for the motion cueing algorithm. The low-complexity explicit controller is formulated for the efficient control of the motion cueing system for the ULTIMATE driving simulator available in Renault.

Keywords: Control of networks
Abstract: Whereas conventional power systems heavily rely on bulk generation by synchronous machines, future power systems will be comprised of distributed generation based on renewable sources interfaced by power electronics. A direct consequence of retiring synchronous generators is the loss of rotational inertia, which thus far was the dominant time constant in a power system, as well as the loss of the generator controls, which are the main source of actuation of the power grid. Prompted by these paradigm shifts, we study the dynamic behavior of a nonlinear and first-principle low-inertia power system model including detailed power converter models and their interactions with the power grid. In this paper, we focus particularly on the admissible steady-state behavior of such a low-inertia power grid and derive necessary and sufficient control specifications for power converters.

Keywords: Sensor networks, Distributed control and estimation
Abstract: Large-scale distributed systems such as sensor networks, often need to achieve filtering and consensus on an estimated parameter from high-dimension measurements. Running a Kalman filter on every node in such a network is computationally intensive; in particular the matrix inversion in the Kalman gain update step is expensive. In this paper, we extend previous results in distributed Kalman filtering and large-scale machine learning to propose a gradient descent step for updating an estimate of the error covariance matrix; this is then embedded and analyzed in the context of distributed Kalman filtering. We provide properties of the resulting filters, in addition to a number of applications throughout the paper.

Keywords: Distributed control and estimation, Estimation and filtering, Control under communication constraints
Abstract: We consider the sparsity-promoting Linear Quadratic Gaussian (LQG) control for a network of linear systems. A sparse LQG controller requires fewer communication channels with the networked system. The bidirectional communication implies that the column-block-sparsity pattern of the Kalman filter and the row-block-sparsity pattern of the state feedback controller must be the same. We develop a two-step procedure: the first step being a sparsity-promoting design of the Kalman filter and the second step leveraging the structure identified in the first step to design the respective controllers. In both steps we employ the Alternating Directions Method of Multipliers (ADMM) and show its effectiveness for the identification and the structural LQG design. In particular, ADMM allows us to decompose the structured LQG problem into a sequence of convex quadratic problems that can be solved efficiently. We demonstrate via numerical experiments that our approach results in sparse controllers whose performance is comparable to that of the fully centralized controllers.

Keywords: Gain scheduling, Input and excitation design, Iterative modelling and control design
Abstract: Matrix optimization problems that contain one or more non-convex quadratic matrix constraints are considered. An iterative solving method is proposed; at each iteration convex matrix sub-problem is formulated and solved using standard Convex Optimization algorithms. Global convergence of the method is proven. Implementation of the method is especially simple if non-convex matrix constraints are concave. The method is applied for solving long-standing problem of the H-infinity design with additional sparsity constraint or objective on the controller.

Keywords: Particle filtering/Monte Carlo methods, Bayesian methods, Multi-agent systems
Abstract: Can a dynamical system paint masterpieces such as Da Vinci's Mona Lisa or Monet's Water Lilies? Moreover, can this dynamical system be chaotic in the sense that although the trajectories are sensitive to initial conditions, the same painting is created every time? Setting aside the creative aspect of painting a picture, in this work, we develop a novel algorithm to reproduce paintings and photographs. Combining ideas from ergodic theory and control theory, we construct a chaotic dynamical system with predetermined statistical properties. If one makes the spatial distribution of colors in the picture the target distribution, akin to a human, the algorithm first captures large scale features and then goes on to refine small scale features. Beyond reproducing paintings, this approach is expected to have a wide variety of applications such as uncertainty quantification, sampling for efficient inference in scalable machine learning for big data, and developing effective strategies for search and rescue. In particular, our preliminary studies demonstrate that this algorithm provides significant acceleration and higher accuracy than competing methods for Monte Carlo, Quasi Monte Carlo, Markov Chain Monte Carlo (MCMC).

Keywords: Multi-agent systems, Cooperative systems, Reachability analysis, verification and abstraction of hybrid systems
Abstract: This paper presents a fully automated procedure for controller synthesis for multi-agent systems under the presence of uncertainties. We model the motion of each of the N agents in the environment as a Markov Decision Process (MDP) and we assign to each agent one individual high-level formula given in Probabilistic Computational Tree Logic (PCTL). Each agent may need to collaborate with other agents in order to achieve a task. The collaboration is imposed by sharing actions between the agents. We aim to design local control policies such that each agent satisfies its individual PCTL formula. The proposed algorithm builds on clustering the agents, MDP products construction and controller policies design. We show that our approach has better computational complexity than the centralized case, which traditionally suffers from very high computational demands. The overall framework is demonstrated in an numerical example.

Keywords: Industrial applications of process control, Advanced control technology, Process modeling and identification
Abstract: N/C Ratio is an important parameter for process optimization occuring in urea synthesis reactor because it affects the amount of produced urea and corrosion to the material in the reactor. In most cases, the measurement of N/C Ratio is performed in the laboratory so that it has quite significant delay time in producing the results of measurement, which is undesired for control and process optimization purposes. This paper proposes a development of inferential measurement system using wavelet network (wavenet) as parameter and inferential estimator. The design was implemented for measuring N/C Ratio using real-time data of an urea synthesis reactor of a fertilizer plant located in East Java. The results show that the parameter estimator has RMSE value of 0.0561 using the flow of ammonia and bottom product temperature of the reactor, whereas the inferential estimator has the RMSE value of 0.0486 with shorter time of estimation of measurement results.

Keywords: Industrial applications of process control, Process control applications, Process modeling and identification
Abstract: An adaptive soft sensor modeling method based on weighted supervised latent factor analysis is proposed. In conventional moving window based adaptive soft sensor, predictive model is constructed only with the latest process information. To fully take advantage of the past windows, a set of recent local models are integrated by the Bayes’ rule for quality estimation. However, the former built models may contain similar information about the process, and the redundancy would increase the calculation with a low-efficient accuracy improvement. Then a selecting method is proposed through a statistical hypothesis testing to determine whether a window dataset should be retained or not. In this way, the mostly informative models are left to integrate an efficient predictive model. A real industrial case demonstrates the feasibility and efficiency of the proposed adaptive soft sensor.

Keywords: Industrial applications of process control, Model predictive and optimization-based control, Real time optimization and control
Abstract: Electric arc furnaces (EAFs) are broadly used in the steel industry for producing different grades of steel by melting steel scrap and modifying its chemistry. The EAF process is highly energy intensive and involves a low level of automation. The decisions associated with the amount and timing of injected inputs depend heavily on the EAF operators. Although the operators' practical experience is crucial in running the EAF, important multivariable interactions and subtle relationships may not be apparent. In this work, a multi-rate moving horizon estimator (MHE) is coupled with an economics-based dynamic optimizer to form an online decision support tool (DST). The tool is able to reconstruct the states and provide optimal decisions to operators in less than 18 CPU seconds on average despite the use of a highly nonlinear large-scale EAF model. This framework is developed using entirely open source tools to have a high appeal to industrial practitioners. A case study is presented which demonstrates the increase in profit through the use of the DST.

Keywords: Industrial applications of process control, Process control applications, Process modeling and identification
Abstract: Although hydrogen is considered as the perfect energy source for the future due to its pollution free operation in fuel cell powered automobile/stationary applications, considerable efforts are still in development to prevent direct on-board storage of the fuel due to several inevitable challenges. On-site production of hydrogen using suitable reforming techniques and purification using membrane separation appears to be an acceptable choice to overcome this challenge. Even though several works have been reported separately on the dynamic and steady state modeling of reformer, membrane separation, and fuel cell subsystems, only very few have discussed the possibility of integrating the units to operate as a single entity. This study addresses the mathematical modeling and dynamic analysis of the integrated reformer membrane fuel cell system to be used in both portable as well as stationary applications. Autothermal reforming, which has the ability to circumvent the heat requirement problem of the endothermic steam reforming, has been selected as the fuel processing subsystem while gas separation using palladium membrane has been considered as a suitable option for hydrogen gas purification. Low temperature polymer electrolyte membrane fuel cell (PEMFC) is the power generation subsystem. A case study of the integrated unit powering a fuel cell vehicle assuming an idealized driving power profile is examined and a suitable control strategy to operate the system based on the load demand has been implemented.

Keywords: Industrial applications of process control, Process control applications, Model predictive and optimization-based control
Abstract: The performance and computational cost of distributed MPC for the control of compressor networks is investigated in simulation. Both cooperative and non-cooperative approaches are considered and compared to the performance achieved with centralized control in the presence of a discharge-side disturbance. Two systems, each with two compressors, are studied: one is arranged in parallel configuration and the other in series. Due to the high degree of non-linearity of both systems, the models are re-linearized at each time step and a linear, delta-input MPC formulation is used. The non-cooperative controller exhibited a significantly reduced computation time relative to the centralized controller (25% and 40% lower for the parallel and serial configurations, respectively), while the cooperative controller did not significantly reduce the computation time. For the parallel configuration, both distributed and centralized controllers had identical control performance. For the serial configuration, only the cooperative controller achieved similar performance to the centralized approach; the noncooperative controller demonstrated a 9% reduction in the minimum surge control distance reached in the downstream compressor.

Keywords: Process control applications, Batch and semi-batch process control
Abstract: An upgrading process to obtain biomethane from biogas is studied, consisting of carbon dioxide removal by an amine-based pelleted solid sorbent inside a fixed-bed tubular reactor. The amine catalyst undergoes a saturation effect, so that a regeneration stage is necessary. In order to ensure continuous biomethane production, the plant automation requires a set of reactors working in parallel. This way, while a reactor is in the adsorption stage, another one is in the regeneration stage. The duration of the stages is such that three reactors at least are needed. Overall, this leads to a cyclic control system. In this paper we develop a dynamic model of the batch process, based on mass, energy and momentum conservation equations and on algebraic constitutive relations. From the initial partial differential equation model, a lumped-parameter description is worked out, leading to a nonlinear system with 280 state variables. Such model is used to understand the adsorption/desorption process in detail and then design a cyclic control structure.

Keywords: Regulation (linear case), Structural properties, Output feedback control (linear case)
Abstract: This work deals with a regulation problem for hybrid linear systems which exhibit a continuous-time state motion, ruled by the so-called flow dynamics, except at isolated points of the time axis, where the state has discontinuities governed by a jump behavior. Jump time instants are not a-priori known and may be unequally spaced, the only admissibility constraint being that the set of the time intervals between consecutive jumps has a fixed positive lower bound. The considered problem consists in finding a hybrid error feedback compensator that forces the output of a given hybrid plant to asymptotically follow a reference trajectory generated by a hybrid exogenous system, while achieving global asymptotic stability of the closed-loop dynamics, for all the admissible sequences of jump times. The problem is investigated from a structural point of view, using geometric notions and properties. A sufficient condition for the existence of solutions is first stated in an implicit form, by considering the overall compensated system. This result is instrumental in giving a sufficient constructive condition which refers to the output-difference connection of the plant and the exogenous generator. The conditions are expressed in terms of hybrid invariant and controlled invariant subspaces of the systems at issue as well as of their stability and stabilizability properties. This approach provides a viable algorithmic procedure for the synthesis of solutions, if any exists.

Keywords: Descriptor systems, Structural properties, Polynomial methods
Abstract: The relationship between the unimodular matrices relating coprime and column reduced matrix fraction descriptions(MFD) of a nonproper transfer function, and the restricted system equivalence (r.s.e.) transformations relating the corresponding generalised state space realisations is considered. It is shown that the r.s.e and unimodular transformations can be directly obtained from each other by inspection. The r.s.e. transformations leading to the canonical form are derived from the unimodular transformations leading to the echelon canonical form of the composite matrix of the MFD of the system.

Keywords: Descriptor systems, Robust control, UAVs
Abstract: This paper discusses a novel implementable approach to an exact linearization procedure based on the implicit systems techniques. The formal procedure we propose includes a specific ``splitting" of the nonlinear state representation in two parts that involve a basic rectangular representation and an auxiliary nonlinear algebraic equation. The proposed linear implicit systems description makes it possible to apply the conventional linear control techniques to an initially given sophisticated nonlinear dynamic model.

Keywords: Structural properties, Linear multivariable systems, Time-invariant systems
Abstract: The problem of characterizing the sequences of matrices that can be realized as the block-matrices of the controllability matrices of controllable systems is considered. Necessary and sufficient conditions for the existence of realizations are provided. It is then shown that when realizations exist they are unique if and only if the rank of the input matrix in the realization is greater than 1. The non-uniqueness of the Single Input realizations is associated with the assignability property of these type of systems. This realization problem is shown to be useful to provide a characterization of the closure of the orbit under similarity when restricted to controllable systems. Finally, the sequences which are realizable as the controllability matrix of controllable systems with prescribed controllability indices is shown to be a differentiable manifold and its dimension is computed.

Keywords: Linear systems, Decoupling problems
Abstract: Morgan's problem, or the row-by-row decoupling of linear systems by state feedback, has attracted control theorists for fifty years. In spite of that, the problem has not been completely solved yet. This paper considers a simple case of Morgan's problem in which the system has already been decoupled and has an integrator dynamics. The objective is to characterize all achievable sets of the decouplability indices (infinite zero orders of the decoupled system).

Keywords: Linear multivariable systems, Output feedback control (linear case), Linear systems
Abstract: The paper is concerned with the improvement of the overall sensitivity properties of a method to design feedback laws for multivariable linear systems which can be applied to the whole family of determinantal type frequency assignment problems, expressed by a unified description, the so-called Determinantal Assignment Problem (DAP). By using the exterior algebra/algebraic geometry framework, DAP is reduced to a linear problem (zero assignment of polynomial combinants) and a standard problem of multilinear algebra (decomposability of multivectors) which is characterized by the set of Quadratic Plucker Relations (QPR) that define the Grassmann variety of P. This design method is based on the notion of degenerate compensator, which are the solutions that indicate the boundaries of the control design and they provide the means for linearising asymptotically the nonlinear nature of the problems and hence are used as the starting points to generate linearized feedback laws. A new algorithmic approach is introduced for the computation and the selection of degenerate solutions (decomposable vectors) which allows the computation of static and dynamic feedback laws with reduced sensitivity (and hence more robust solutions). This approach is based on alternative, linear algebra type criterion for decomposability of multivectors to that defined by the QPRs, in terms of the properties of structured matrices, referred to as Grassmann Matrices. The overall problem is transformed to a nonlinear maximization problem where the objective function is expressed via the Grassmann Matrices and the first order conditions for optimality are reduced to a nonlinear eigenvalue-eigenvector problem. Hence, an iterative method similar to the power method for finding the largest modulus eigenvalue and the corresponding eigenvector is proposed as a solution for the above problem.

Keywords: Mechatronic systems, Motion Control Systems
Abstract: Manufacturing equipment often consists of multiple subsystems. For instance, in lithographic IC manufacturing, both a reticle stage and a wafer stage move synchronously. Traditionally, these subsystems are divided into manageable subproblems, at the expense of a suboptimal overall solution. The aim of this paper is to develop a framework for overall system performance improvement. The method pursued in this paper builds on traditional designs, and extends these through a bi-directional controller coupling. The aim here is to optimize a criterion that specifies overall system performance. To achieve this, a new parameterization that relates to the Youla parameterization is developed that connects the bi-directional controller parameter affinely to the overall control criterion, which enables a systematic design. The performance improvement is confirmed in a case study using measured data from an industrial wafer scanner.

Keywords: Motion Control Systems, Mechatronic systems, Identification and control methods
Abstract: In an attempt to surpass Bode's gain-phase relationship, a hybrid integrator-gain system is studied that has significantly less phase lag in its describing function description when compared to a linear integrator. The hybrid integrator is designed to obtain improved low-frequency disturbance rejection properties under double-integrator (PI²D-like) control, but without the unwanted increase of overshoot otherwise resulting from adding an extra linear integrator. Closed-loop stability of the hybrid control design is guaranteed on the basis of a circle-criterion-like argument and checked through (measured) frequency response data. Closed-loop performance is obtained by data-driven optimization using gradients derived from a state-space description of the hybrid integrator, frequency response data from the linear part of the control system, and data obtained from machine-in-the-loop measurement.

Keywords: Vibration control, Motion Control Systems, Identification and control methods
Abstract: In digital/sampled-data motion control systems, the system outputs are only available at certain rates. This sets a great challenge to high-precision motion control systems that subject to high-frequency disturbances, since the feedback regulator cannot directly observe the inter-sample outputs. To handle such situations, a robust multirate control approach is proposed in this paper to enhance disturbance attenuation at high frequencies, including those, under certain conditions, near and beyond the Nyquist Frequency. First, based on the Youla parameterization of all stabilizing controllers, an add-on compensator based on multirate observer is constructed using the a priori nominal model of the disturbance dynamics. Then robust design of a proper Q filter is formulated via the theory of multiple-input-multiple-output (MIMO) robust control, which guarantees the closed-loop stability in the presence of norm-bounded model uncertainties. Effectiveness of the proposed algorithm is evaluated by simulations on a hard disk drive (HDD) benchmark problem, where the inter-sample position errors are approximately recovered and high-frequency disturbance is greatly attenuated with guaranteed closed-loop stability.

Keywords: Identification and control methods, Modeling, Mechatronic systems
Abstract: We provide Model Predictive Control (MPC) formulations for the advanced control of high-precision track-following servo systems to improve rejection of noisy, measurable disturbances. This work develops a disturbance prediction method using the wavelet denoising technique and system identification, which is used to anticipate the disturbances in the system using preview measurements. The MPC formulations allow for improved track following and disturbance rejection when compared to classical control techniques. We consider l_1 and l_2 formulations of the MPC problem to assess and compare tracking performance and computational complexity as a function of the prediction horizon. These advanced control techniques are simulated on a reel-to-reel tape drive system model to demonstrate the ability of these algorithms to perform precise track following and disturbance rejection while assessing implementation techniques that can yield fast computation times that this application demands.

Keywords: Identification and control methods, Motion Control Systems
Abstract: Frequency domain identification of system parameters and time delay is essential for model-based motion control of dynamic systems. Conventional approaches incorporate the delay into the model through an explicit model parametrization, which results in a high amount of non-local minima. In this paper, a new strategy is proposed based on a two-stage frequency domain approach to linearly incorporate the delay in the parameter vector of the system. This enables the proposed method to accurately identify both the time delay and system parameters. In a first stage, the system is parametrized and the delay is approximated using rational (all-pass) orthonormal basis functions. The resulting constraints on the individual delay approximation parameters are relaxed through a general all-pass constraint which is enforced iteratively by reformulating the identification algorithm. In a second stage, the continuous time delay term is identified in a convex problem with fixed system parameters using the previous approximates as starting values. Finally, simulations and experimental results validate the effectiveness of this new two-stage method.

Keywords: Identification and control methods, Motion Control Systems, Design methodologies
Abstract: Iterative learning control (ILC) is widely used as a simple method for precise tracking of systems under repetitive conditions. ILC operates by ``learning" from the previous iteration's errors, correcting them over a number of iterations. However, the question of whether or not a nonlinear ILC system converges is still in general an open one. Assuming a state-space formulation, we use contraction analysis to formulate a convergence condition for ILC system as a linear matrix inequality (LMI). Finally, we compute a convergence certificate for a simple example involving ``anticogging" a permanent-magnet synchronous motor driving a pendulum in simulation.

Keywords: Micro and Nano Mechatronic Systems, Vibration control, Motion Control Systems
Abstract: We present a new digital design of Q-control, i.e. controllable change of cantilever quality factor, oriented on digital implementation at FPGA. The designed Q-controller changes the amplitude and phase of cantilever excitation based on amplitude and phase of the deflection signal measured by digital lock-in amplifier. This significantly differs from conventional design , where effective Q-factor is modified by adding a self-excitation force proportional to the cantilever deflection of an earlier time. New digital Q-control algorithm is justified by flexible beam asymptotic models based on Euler-Bernoulli equation and Krylov-Bogoliubov-Mitropolsky averaging technique. Many controversial features of Q-control can now be verified by the models. In contrast to conventional implementation that requires additional hardware electronics, our design is implemented at FPGA in parallel with many other control and signal processing algorithms. The ability of Q-control to decrease tip-sample interaction with higher effective Q and increase it with lower one is illustrated on the automatic landing (soft approach) of the tip with minimal indenting of the sample surface, or damaging the tip.

Keywords: Vibration control, Identification and control methods, Mechatronic systems
Abstract: In this paper, a data driven controller is designed for the positioning control of a piezoelectric tube scanner (PTS) used in an atomic force microscope (AFM). A single-input single-output (SISO) model-based data driven controller is synthesized by using a mixed negative imaginary (NI) and small gain (SG) approach. The controller is implemented on an AFM and gives significant damping and tracking performance, with 16.64 dB and 19.33 dB damping at the resonance frequency of the X and Y-axes of the PTS, respectively. Moreover, this type of controller design is an effective approach to give intuition about how the controller frequency response should, depending on the design constraints being applied, which ensures optimized performance in vibration control.

Keywords: Vibration control, Micro and Nano Mechatronic Systems, Modeling
Abstract: Piezoactuated nanopositioners are an integral component in Scanning Probe Microscopes (SPM). The imaging application of SPMs necessitate the loading of the nanopositioning platform with various samples. This causes an increase in mass thereby altering the dynamics of the system. Various methods have been proposed to control uncertain systems such as H-infinity robust control, mu-synthesis and mixed mu-synthesis. Additionally, low-order damping controllers, such as Integral Resonance Control (IRC) and Positive Position Feedback (PPF), have been shown to be robustly stable via the negative imaginary lemma. In this paper, IRC is used as a benchmark for robust performance, and robust controllers are developed using the aforementioned methods. It is found that the best performance, in terms of the H-infinity norm over the range of uncertainty, is achieved using the IRC control scheme. In addition, IRC provides more accurate tracking of a reference signal.

Keywords: Micro and Nano Mechatronic Systems, Motion Control Systems, Microsystems: nano- and micro-technologies
Abstract: Scanning probe microscopy (SPM) technology plays the irreplaceable role in investigating micro/nano world, which has been bringing tremendous development opportunities to various fields. To enhance maneuverability, SPM can be modified into a nanomanipulation system with its scanning probe as the end-effector. The probe is commonly mounted on smart material based actuators to generate precise motion with nanometer level resolution. However, instinctive hysteretic characteristics ubiquitously exist in smart material actuators, which degrade their arbitrary positioning precision. To effectively represent and further reduce complex hysteretic effects, this paper proposes to utilize the modified Prandtl-Ishlinskii (PI) model: extended unparallel PI (EUPI) model, which possesses advantages such as the flexible modeling capability (compared to the prevalently implemented modified PI models) and the easy-to-use property for construction and identification (compared to the well known Preisach model and the Generalized PI (GPI) model). To effectively reduce complex hysteresis, the EUPI model based compensator (IM_UPI compensator) is required to be flexible and precise. To efficiently design such a compensator satisfying stability requirement, this study proposes a systematic approach, including stabilizing gain selection and analytical calculation of boundary gains of the EUPI irreversible component. As a demonstration, satisfactorily precise IM_UPI compensator was established according to this systematic design approach and tested through simulations on rectifying Atomic Force Microscopy (AFM, one special SPM) imaging process distorted by complex hysteresis.

Keywords: Motion Control Systems, Identification and control methods, Vibration control
Abstract: A plant with unstable zeros is known to be difficult to control because of initial undershoot of step response and unstable poles in its inversion system. There are two reasons why a plant has unstable zeros in the discrete time domain: 1) non-collocation of actuators and sensors, 2) discretization by zero-order-hold. Problem 2) has been solved by the perfect tracking control (PTC) method based on multirate feedforward control proposed by our research group. However, the conventional PTC method cannot achieve the perfect tracking for a plant with continuous time unstable zeros generated by 1) because of the divergence of the desired state trajectories. Preactuation Perfect Tracking Control (PPTC) method proposed by our group solves problem 1) by the state trajectory generation based on a time axis reversal. This paper verifies the effectiveness of PPTC by simulations and experiments in comparison with several single rate feedforward control methods.

Keywords: Smart Structures, Identification and control methods, Design methodologies
Abstract: This article describes a method for tracking control of monolithic nanopositioning systems using integrated piezoelectric sensors. The monolithic nanopositioner is constructed from a single sheet of piezoelectric material where a set of flexures are used for actuation and guidance, and another set are used for position sensing. This arrangement is shown to be highly sensitive to in-plane motion (in the x- and y-axis) and insensitive to vertical motion, which is ideal for position tracking control. The foremost difficulty with piezoelectric sensors is their low-frequency high-pass response. In this article, a simple estimator circuit is used to allow the direct application of integral tracking control. Although the system operates in open-loop at DC, dynamic command signals such as scanning trajectories are accurately tracked. Experimental results show significant improvements in linearity and positioning error.

Keywords: Dynamics and control
Abstract: Ergodicity and output controllability have been shown to be fundamental concepts for the analysis and synthetic design of closed-loop stochastic reaction networks, as exemplified by the use of antithetic integral feedback controllers. In [Gupta, Briat & Khammash, PLoS Comput. Biol., 2014], some ergodicity and output controllability conditions for unimolecular and certain classes of bimolecular reaction networks were obtained and formulated through linear programs. To account for context dependence, these conditions were later extended in [Briat & Khammash, CDC, 2016] to reaction networks with uncertain rate parameters using simple and tractable, yet potentially conservative, methods. Here we develop some exact theoretical methods for verifying, in a robust setting, the original ergodicity and output controllability conditions based on algebraic and polynomial techniques. Some examples are given for illustration.

Keywords: Kinetic modeling and control of biological systems, Dynamics and control, Microbial technology
Abstract: Degradation of proteins in cells plays a large role in the dynamics of gene networks. This degradation is enabled by proteases, which are found in limited quantities in the cell. Proteins that compete for protease may therefore become coupled by non-explicit interactions, which are often neglected in mathematical models. In this work, we develop a model for these non-explicit interactions in gene networks. We examine the effects of protease sharing on the number of equilibria of a system and on the steady state protein concentrations. As a consequence of this analysis, we find that protease sharing effects may be used to cancel undesirable effects due to ribosome sharing.

Keywords: Dynamics and control, Modeling and identification
Abstract: Synthetic Biology is an emerging field at the interface of biology and engineering, concerned with the design and implementation of synthetic biological parts, devices and systems. With applications ranging from industrial biosynthesis of chemicals to treatment and prevention of disease, Synthetic Biology holds great promise, but faces several challenges due to the uncertainties and noise inherent in biological systems. In this paper we review recent progress in the design and testing of biological control systems that aim to overcome these limitations. We then use classical control theory to derive a number of design constraints for implementation of linear control systems that achieve adaptation and disturbance rejection. Finally, we design a linear system for rejection of ramp-type disturbances, and from this demonstrate how the derived linear system constraints can be embedded in a more realistic non-linear biological context.

Keywords: Dynamics and control, Modeling and identification, Integrated bioprocessing
Abstract: Biological counterparts of differential operators are not only likely to exist in natural systems but also desirable to realize as modules in synthetic biology. Therefore, we present a genetic regulatory network which approximates the differential operator. For the textit{in silico} design, we use a modeling framework which takes into account the limitations imposed by finite pools of resources; we synthesize the differentiator module by combining genetic regulatory parts which realize basic input/output functions such as a gain, integrator and signal difference. The resulting two-gene-network approximates the transfer function of a differential operator with additional low-pass filter. The functionality of this small network, as well as its robustness towards changes in the cellular environment, is investigated numerically.

Keywords: Modeling and identification, Dynamics and control
Abstract: Two of the most common pattern formation mechanisms are Turing-patterning in reaction-diffusion systems and lateral inhibition of neighboring cells. In this paper, we introduce a broad dynamical model of interconnected cells to study the emergence of patterns, with the above mentioned two mechanisms as special cases. This model comprises modules encapsulating the biochemical reactions in individual cells, and interconnections are captured by a weighted directed graph. Leveraging only the static input/output properties of the subsystems and the spectral properties of the adjacency matrix, we characterize the stability of the homogeneous fixed points as well as sufficient conditions for the emergence of spatially non-homogeneous patterns. To obtain these results, we rely on properties of the graphs (bipartiteness, equitable partitions) together with tools from monotone systems theory. As application example, we consider pattern formation in neural networks to illustrate the practical implications of our results. Our results do not restrict the number of cells or reactants, and do not assume symmetric connections between two connected cells.

Keywords: Model formulation, experiment design, Biomedical system modeling, simulation and visualization, Cellular, metabolic, cardiovascular, pulmonary, neuro-systems
Abstract: We describe an ultrasensitive reaction network to achieve closed loop control of biomolecular systems. This network is based on non-cooperative interactions of activator and inhibitor species that regulate the controller output level with a mechanism similar to protein phosphorylation. The controller reactions could potentially be realized using nucleic acids or monomeric proteins. Using numerical analysis we demonstrate that ultrasensitivity of the controller output renders the closed loop system robust to perturbations in the system parameters.

Keywords: Modeling and simulation of power systems, Real time simulation and dispatching, Test and documentation
Abstract: Many studies on power and mechanical hardware-in-the-loop (HiL) systems emphasise the importance of stability and accuracy issues. These are especially crucial for full-scale HiL systems, because their actuators, linking virtual and real parts, must not be neglected in the design of the overall system. In this paper, we propose a general, control-based strategy with a simple two-step design procedure. First, an inner control loop is designed to provide an appropriate input interface to the hardware part including said actuators. Then, the virtual software part is connected to the hardware using the notion of internal model control. A finding is that, in principle, the choice of interface directions does not matter when an inner control loop is needed because of the non-negligible actuator dynamics. Furthermore, it is demonstrated how the proposed control strategy allows for directly integrating existing software models. A simulation example with a large dynamometer for testing nacelles of wind turbines is presented to illustrate the methodology.

Keywords: Control system design, Real time optimization and control, Control of renewable energy resources
Abstract: ReReal-time simulation and in particular power hardware-in-the-loop (PHIL) technology allows for the testing of power electronic inverters acting as grid-connected generation units in a simulation environment that closely mirrors existing and future smart grid networks. The interface between the real-time simulation model and physical devices is a system theoretic challenge as its design implies significant impact on both stability and accuracy of the real-time control system. In general, small time steps of the PHIL simulation model support either way stability and accuracy and these limitations are defined by well-given real-time constraints by the digital real-time simulator (DRTS). Different interface designs address this issue by using a minimum time-step at the power interface (PI) in combination with applying a staged adaptation related to stability for the digital model in accordance with given real-time constraints. The stability of the resulting closed-loop PHIL simulation system is verified by means of the classical Nyquist stability criterion. A test setup is built up with multiple photovoltaic inverters connected to different nodes within a distribution network and investigations of the behaviors of active and reactive power delivery with respect to the P-Q trajectories are discussed. Simulation results with different interface topologies are compared with waveforms obtained by a hardware test setup with the same network configuration. Statements on interactions of the inverter control algorithms and the impact on the grid voltage stability can be made and represent a basis for future analysis of smart grid testing platforms.

Keywords: Process control applications, Analysis of reliability and safety
Abstract: Energy management of multi-source vehicles is a complex task. The higher the number of sources becomes, the higher the complexity is. Moreover, the energy management strategies have to face real-time issues. As a consequence, it is important to find some testing procedures to assess the developed strategies, in real-time conditions before implementation in the vehicle. In this paper, a Power Hardware-In-The-Loop simulation is implemented for a Fuel Cell – battery – Supercapacitors vehicle. The set-up enables to test some Energy Management Strategies in real-time conditions.

Keywords: Application of power electronics, Real time simulation and dispatching, Test and documentation
Abstract: In power hardware in the loop (PHIL) setups, the device under test (DUT) is connected to the rest of the system (ROS) running in a real-time simulator through an Interface Algorithm (IA) and power amplifier, which strongly influences stability and accuracy of the test setup. This paper presents a comprehensive theoretical framework for the analysis of the two aspects of a PHIL system with different IAs, and demonstrates its applicability to the design of PHIL test benches for wind turbines. For the theoretical modelling derivation, the interaction of two lumped active systems is considered.

Keywords: Modeling and simulation of power systems, Real time simulation and dispatching, Control of renewable energy resources
Abstract: In this contribution a mechanical-level Hardware-in-the-Loop system based on a Model Predictive Controller, for a 4MW system test bench is proposed. An experimentally validated model of this test bench is introduced and the basis of the mechanical-level Hardware-in-the-Loop system. The main purpose of that system is to emulate the inertia and eigenfrequency of the wind turbine’s drive train at the system test bench, where the rotor is dismounted and hence the eigenfrequencies are altered. The results show that, with realistic motor torque constraints being considered and the original wind turbine controller activated, the proposed concept allows to reproduce the first two eigenfrequencies accurately. Beyond that the transmission behavior from pitch angle to generator speed of the wind turbine at the test bench and of the unmodified, real wind turbine match up to a frequency of 9Hz in the nominal case. Even with parameter deviations of up to 20% and time-delay of 15ms the frequency response match up to 7Hz.

Keywords: Power systems stability, Optimal operation and control of power systems, Real time simulation and dispatching
Abstract: Evaluation of system level control functions is an essential step for de-risking implementation in the field. Hardware in the loop (HIL) simulation can play a critical role in accomplishing this goal. In the context of all electric navy ships, additional emphasis must be given to fully represent the interconnection between the power distribution system and various high power and often pulsating loads. This extended abstract illustrates facilities established at the authors’ institution to serve the US navy’s needs for such HIL based evaluation of controls functions. In addition, we provide a brief outlook towards a planned expansion of the capabilities within the next year.

Keywords: Intensive and chronic care or treatment, Monitoring
Abstract: Health status monitoring for critically ill patients can help medical stuff quickly discover and assess the changes of disease and then take appropriate treatment, which is of great clinical significance. In this study, a data-driven learning approach called LWPR-PCA is first applied to monitor health status of patients in intensive care unit (ICU). Locally weighted projection regression (LWPR) is used to approximate the complex nonlinear process by using local linear models, and then principal component analysis (PCA) is further applied to status monitoring. LWPR-PCA is a good candidate to establish an individual-type model for an ICU patient and to improve the global monitoring performance, which is the mainstream direction of modern medicine. To confirm the superiority of LWPR-PCA, physiological data of 18 ICU patients are collected, of which the mean fault detection rates (FDRs) are increased by 4.8% and 4.6%, and the mean fault alarm rates (FAR) are decreased by 6.7% and 5.9% in terms of two kinds of faults, compared to the latest reported method L-PCA, which combines just in time learning and modified PCA methods.

Keywords: Biomedical system modeling, simulation and visualization, Artificial pancreas or organs, Control of physiological and clinical variables
Abstract: Sensor faults in an articial pancreas (AP) system for people with type 1 diabetes (T1D) can yield insulin infusion rates that may cause hypoglycemia or hyperglycemia. New statistical process monitoring methods are proposed for real-time detection of sensor-related faults in AP systems to mitigate their effects. Remodulated dynamic time warping for synchronization of signal trajectories and Savitzky-Golay filter for calculation of real-time numerical derivatives are integrated with multiway principal component analysis. Data from 14 subjects that participated in 60 hours of closed-loop AP experiments with variations in meals and physical activity levels and times are used. Glucose measurements from a continuous glucose monitoring sensor are monitored for fault detection. The results illustrate that the proposed method is able to detect various types of unexpected dynamical changes or faults, and label them correctly. There were no missed faults in any tested cases. The algorithm can inform AP users about sensor faults and unexpected changes, and provides valuable information to an AP for prevention hypoglycemia or hyperglycemia that may be caused by sensor faults.

Keywords: Bio-signals analysis and interpretation, Developments in measurement, signal processing, Decision support and control
Abstract: Searching for similarity between time series plays an important role when large amounts of information need to be clustered to integrate intelligent supported personal health care diagnosis systems. The performance of classification, clustering and disease prediction are influenced by the prior stage where similarity between time series is performed. Physiologic signals vary even within the same patient, so an analysis of their possible variation without affecting future clustering accuracy is hereby addressed. Commonly employed methods of measuring similarity between time series were tested on longer data segments than the typical cardiac cycle envisaging its use integrated on personalized health care cardiovascular diagnosis systems. Euclidean distance, Discrete Wavelet Transform, Discrete Fourier Transform, Correlation Coefficient, Mahalanobis distance, Minkowski Distance, and Dynamic Time Warping Distance were compared when 20 levels of small variations in amplitude scaling and shift, time scaling and shift, baseline variance and additive Gaussian noise are forced to the tested time series. Concentrating on the performance of the similarity methods in terms of their insensibility to small data variations results demonstrate that the time domain Correlation Coefficient is the most robust method while the Discrete Wavelet Transform is the elected one between the transform-based methods tested. Selection of a similarity method to be applied should also take into account implementation issues, namely need of data reduction to avoid computational burden, and in this case transform-based methods should be elected.

Keywords: Model formulation, experiment design, Cellular, metabolic, cardiovascular, pulmonary, neuro-systems
Abstract: Ghrelin, a peptide hormone, occupies a crucial role in food intake control. Differently from other hormones contributing to energy homeostasis, usually exerting their regulating action by signaling satiety (e.g. leptin), ghrelin is known to stimulate appetite and, in general, to upsurge the propensity of animals to seek out food and start eating. Medical and experimental literature has shown that approximately 70-80% of ghrelin production occurs in the stomach, whilst the great part of ghrelin control, leading to ghrelin suppression soon after a meal administration, is exerted by signals originated in the small intestine. This note proposes a mathematical model for ghrelin dynamics, focusing the attention on its short-term 24 hours dynamics. The proposed model conforms to the established physiology by introducing a minimal multi-compartmental structure of the gastrointestinal tract. Model parameters are set in order to fit plasma ghrelin concentration data taken from the literature, related to an experiment in humans: simulation-based ghrelin predictions provide promising results if compared to real data. Besides to offer a proper description of the short-term ghrelin dynamics, the model can be thought of as a module of a bigger multi-compartmental structure, aiming to account for the ``web of hormones'' (including, e.g., leptin and insulin) related to food intake and energy homeostasis.

Keywords: Physiological Model, Control of physiological and clinical variables, Decision support and control
Abstract: Ultrafast body cooling of mammals can be achieved by ventilating the lung with a breathable liquid during total liquid ventilation. The instilled liquid into the lung allows to cool the arterial blood temperature, and consequently the organs. While total liquid ventilation can rapidly cool animals, the speed of cooling in humans remains unknown. The problem is to predict the efficiency and safety of the method for humans. The method is based on a previously published mathematical thermal model of mammals in total liquid ventilation. The thermal model is projected to humans. A direct optimal control under constraints is computed to predict the hypothermia induction speed and the sensitivity to parametric uncertainties. The simulated results in human adults illustrate that a worst case optimal control can be used to compute a robust solution in regards to uncertainties of cardiac output and thermal dead volume. In certain patients, brain temperature would reach mild hypothermia in maximum 10~min, with the majority of patients reaching it within 6~min. Hence, the direct optimal control is a potential candidate for the ultrafast therapeutic hypothermia induction for cardio- and neuroprotection of post-cardiac arrest patients.

Keywords: Model formulation, experiment design, Identification and validation, Artificial pancreas or organs
Abstract: This work presents a systematic way to assist on the commissioning of the Predictive Functional Control (PFC) algorithm to be implemented in the context of the Artificial Pancreas (AP) for patients with Type 1 Diabetes Mellitus (T1DM). PFC has demonstrated its high potentiality in process industry since several decades ago. Its use for AP has been specifically adapted and tested in the well validated model of the endocrine system, known as the Uva/Padova model. Firstly, the tests were done in silico using the parameters of 30 patients: 10 children, 10 adolescents and 10 adults. The performance of the controller was evaluated by means of the Control Variability Grid Analysis (CVGA) giving excellent results. We propose here the use of data driven models, as a second step, to perform a PFC final tuning to be practically ready to use in AP implementations. The closed loop responses are tested through dynamic simulations with the obtained models when different meals intake and insulin dosage are given to the patient Nº 5004 from the Center of Diabetes Technology (UVa/USA). In this paper an ARX model is build based on the patient's own historical data recorded during 27 days. The ARX model was used giving good results such as 98.2% of FIT, RMSE=0.75 mg/dl, and the Clarke Grid 100% at Zone A. The simplified models used in the PFC structure were obtained from the ARX model to isolate the insulin impact from the carbs effects on the blood glucose variations. Finally, the full closed loop simulations, taking into account the constraints related to the insulin pump, were performed to conclude the PFC design. Closing the work, comparisons between the blood glucose behavior with and without PFC are given to drive the final conclusions and discuss future works.

Keywords: Engine modelling and control, Modeling, supervision, control and diagnosis of automotive systems
Abstract: In the search for improved performance and control of combustion engines there is a search for the sensors that gives information about the combustion profile and the state of the gases in the combustion chamber. A particular interest has been given to the potential use of the cylinder pressure sensor and there is quite a lot of work that has been made in this area. This paper provides a comprehensive list of references and summarizes applications and methods for extracting information from the cylinder pressure sensor about the combustion and the gas state. The summary highlights the following topics related to cylinder pressure: measurement chain, cylinder torque, extraction of the burn profile, combustion placement, knocking, cylinder air mass, air to fuel ratio, residual gas estimation, and cylinder gas temperature estimation. The focus in the summary is on the latter topics about the gas state but thermodynamic analysis of the combustion process also gets a longer treatment since many methods for information extraction rely on the thermodynamic properties.

Keywords: Engine modelling and control
Abstract: Turbocharging is an important part of engine downsizing. Today, the control of the air charge system often consists of single-input single-output systems, where one input controls one output. With the increasing demand of lowering the emissions it is believed that solutions as long route exhaust gas recirculation and multiple stage turbocharging will be introduced for gasoline engines. This adds more actuators to the air charge system making it a multiple-input system. In the paper the implications of turbocharger speed measurement on the boost control system are investigated. A controller with turbo speed measurement, and one controller without is developed and implemented in a turbocharged inline four gasoline engine equipped with an electric servo-actuated wastegate in an engine test bench. The controllers' ability to control the boost pressure is then discussed.

Keywords: Engine modelling and control, Nonlinear and optimal automotive control, Modeling, supervision, control and diagnosis of automotive systems
Abstract: In order to balance emissions accurately during highly transient engine operation, novel approaches of diesel engine control must achieve an appropriate interplay of the cycle-by-cycle fuel injection, i.e. the start position and mass of each fuel injection pulse, and the air system control scheme. Accordingly, this paper proposes a control concept that adjusts the fuel injection parameters as manipulated variables in dependence of the transient air system dynamics. The approach is based on a cylinder model that predicts the emissions and torque by means of physical and Gaussian Process Regression models. Fuel injection adjustments are determined by numerical optimization to minimize emissions while providing the desired engine torque. The optimization also considers the uncertainty of the emission predictions. This controller is tested by a high fidelity reference engine model which is also briefly introduced. It combines the cylinder description with a 1-dimensional air system model built up in the simulation environment GT-suite. The entire engine model is parametrized and validated using test-bench measurements.

Keywords: Hybrid and alternative drive vehicles, Engine modelling and control, Control architectures in automotive control
Abstract: Todays vehicle industry is converging more and more to electrification of vehicles, introducing electrical architectures to cooperate side by side with the combustion engine. This paper investigates the potential of using an electric turbocharger in a long haulage application during highway driving. A charge sustainable control strategy is developed, implemented, tuned, and evaluated on a heavy duty truck model. The benefits of using an electrical turbocharger on a heavy duty diesel truck, from a long haulage perspective, are evaluated. By calibrating the implemented controller, long haulage driving routes can be charge sustainable and consume less fuel than a conventional truck with fix turbine geometry, the fuel savings for the simulated case is 0.9%.

Keywords: Automotive system identification and modelling, Vehicle dynamic systems, Modeling, supervision, control and diagnosis of automotive systems
Abstract: This paper presents an integrated estimation scheme for the effective engine torque in automotive systems. This leads to a cascaded estimation structure, composed of an adaptive parameter estimator for the augmented wheel dynamics and the longitudinal motion, and an unknown input observer for the engine crankshaft dynamics. The adaptive parameter estimator has the ability to track time-varying parameters and can therefore provide an estimate of the driving torque for the wheels. Then this estimated torque is transmitted to the engine as the load torque through the drivetrain, and is used to design the unknown input observer. The standard models of driveline and tyre friction are modified for ease of parameter estimation. Only the engine crankshaft velocity, the wheel rotational velocity, and the vehicle longitudinal speed are needed. The convergence of these estimators is analyzed. Simulations based on a dynamic simulator built with commercial vehicular simulation software, IPG CarMaker, and Matlab/Simulink show promising results.

Keywords: Hybrid and alternative drive vehicles, Control architectures in marine systems, Engine modelling and control
Abstract: In this work, the problem of energy management strategies in hybrid diesel-electric marine propulsion systems is investigated with the implementation of two types of Model Predictive Controllers. The system behavior is described by models based on system identification as well as on first-principles. These models were used for the design of linear and adaptive predictive controllers respectively. The controllers were successfully tested at HIPPO-1 testbed, at the Laboratory of Marine Engineering, evaluating diverse strategies for disturbance rejection, system stability, and operation of the plant within desirable limits.

Keywords: Optimal operation and control of power systems, Control system design, Power systems stability
Abstract: This paper proposes a compact boiler-turbine control scheme for the fossil-fuel power plants. Generally, control strategies used in boiler-turbine units are implemented as the hierarchical structures consisting of an upper economic optimization layer and a separate lower feedback control layer. The deficiency of such hierarchy is that the tracking of the steady-state set-points, that are computed by the upper layer, is accomplished by the lower layer in an economically non-optimal way. To improve the economic performance of boiler-turbine units, the proposed control scheme integrates plant economic optimization into the dynamic feedback controller output computation process. The stability (and also feasibility) of the proposed control scheme is proven. The effectiveness of the latter is also demonstrated through the 160 MW oil-fired boiler-turbine unit simulation.

Keywords: Model predictive and optimization-based control, Neural networks in process control, Advanced process control
Abstract: In modern real-time unit load scheduling, it is unavoidable for large-capacity supercritical (SC) units to participate in peak-load regulation with automatic generation control (AGC), which raises the requirements for load control of a large SC power unit. With only the traditional coordinated control system, it is easy to fail in meeting the requirements of rapid load-changing and cause large fluctuations for main steam pressure and temperature. Condensate throttling technique, as an emerging new technology for rapid adjustment of unit load, has attracted much attention in recent years. This paper develops a neural network based unit load prediction model which takes condensate throttling into account for a 600 MW SC power unit. An intelligent dual optimization approach is then developed, which uses the load prediction model twice, first to optimize the deaerator valve opening during the initial load-changing stage for fast load following, and then to optimize the turbine valve opening during the later condensate flow recovery phase to keep the load-following accuracy. Simulation tests show that the proposed approach can greatly improve the unit load dynamic response in speed and control accuracy, thus effectively improve the unit load adaptability to AGC.

Keywords: Intelligent control of power systems, Modeling and simulation of power systems, Control of renewable energy resources
Abstract: Wind energy has many advantages, because it does not pollute and is an inexhaustible source of energy. The Double Fed Induction Generator (DFIG) is the most important generator used for Horizontal Axis Wind Turbine (HAWT). In this paper, a nonlinear controller is designed based on the Neural Input-Output Feedback Linearization Control ( N-IOFLC) for DFIG, to force the rotor currents to track specified reference defined form the desired active and reactive stator powers, using the fourth order model of the doubly-fed induction machine in (d, q) axis reference frame with stator currents and rotor currents components as state variables. The neural controller is based on a Recurrent High Order Neural Network (RHONN), trained with an Extended Kalman Filter (EKF). The RHONN works as an identifier to obtain an accurate model which is robust to disturbances and parameter variations. The DFIG stator is directly connected to the grid; the rotor is connected via a back to back converter. Computer simulation results obtained, using Matlab/Simulink⋆, confirm the validity and effectiveness of the proposed control approach.

Keywords: Control system design, Control of renewable energy resources, Nonlinear process control
Abstract: Proper temperature control of Proton Exchange Membrane Fuel Cell is a crucial factor for optimizing fuel cell performance. This paper describes a model-based characterization of the equilibrium points of an open-cathode fuel cell system. Phase plane analysis of the nonlinear model versus a linearized model around different points of operation shows the potential of approximating the nonlinear system behavior with a linear model. Finally, a controller is proposed using robust control techniques is proposed.

Keywords: Constraint and security monitoring and control, Control system design
Abstract: This paper addresses the concept of a bias injection cyber-attack on the load frequency control loop of a single-area power plant. The system evolves in the discrete-time domain and a convex and compact set of polyhedral state constraints represents a valid domain of safe operation under the effect of a stabilizing output-feedback controller. Whenever the safety constraints are violated, an alarm alerts the control center to a security breach. An attacker gains access to frequency sensor measurements and corrupts the data transferred to the automatic generation control unit. The objective of the adversary is to drive the electrical frequency to a safety-critical steady-state value without triggering an alarm. An analysis based on robust invariance concepts assesses the vulnerability of the system on this particular scenario and determines the maximal impact that such an attack can have without activating an alarm. Simulation studies highlight the effect of the cyber-attack on the physical plant.

Keywords: Optimal operation and control of power systems, Modeling and simulation of power systems, Control system design
Abstract: Equation-based, object-oriented dynamic modelling of power generation systems using Modelica is now well-established for simulation purposes. To which extent it can be used for optimal control purposes is still an open research question. In this paper, a realistic Modelica model of a combined cycle plant is developed using Modelica, and then used to formulate and solve the nonlinear control problem of optimal start-up with thermal stress constraints using three different methodologies, all based on direct collocation, implemented in two different tools. The model used in this paper is much more accurate than the one used in previous similar studies. The positive result obtained allow to gain confidence on potential of direct use of Modelica models for optimal power plant control studies.

Keywords: Disturbance rejection
Abstract: The paper explores and compares the closed-loop behavior of conventional Model Predictive Control (MPC) and Repetitive Model Predictive Control (RMPC) in the presence of unknown, highly transient disturbances which are periodic in time. Since MPC applies information about future disturbances when predicting the future response of the system to be controlled, the presence of unknown and transient disturbances, may decrease the quality of the prediction and thus also the performance of the MPC-controlled system significantly. If the disturbance is periodic in time, however, this problem can be attenuated. RMPC approaches the loss of prediction precision by integrating output measurements from past periods to the future forecast. The paper reviews both MPC algorithms for linear systems briefly and compares them experimentally to each other by means of regulating a compressor stator vane flow with transient, periodic disturbances while respecting the input and output constraints of the system.

Keywords: control of fluid flows and fluids-structures interactions, Observers for linear systems, Robust control (linear case)
Abstract: The control using global modes is well suited for the feedback stabilization of oscillatory fluid systems, since it takes into account the unstable dynamics responsible of perturbations growth. The unstable subspace is of small dimension and, most of the time, sufficient to obtain good control performances. But, when an estimator is considered, modeling the high-dimensional stable part is required to ensure consistency between measurement and estimation. The stable part is classically approximated by Galerkin projection onto a well suited basis. Balanced truncation modes or balanced POD are often preferred to global mode's selection, mainly for their ability to approximate input-output behaviors. In this paper, we avoid the Galerkin approximation and we model the effect of the stable part in the observation by an integral term whose associated kernel is of small dimension and easy to pre-compute. This method guarantees the stability of the compensated system and improves its H-infinity performance. Moreover, we give some guidelines to select additional stable modes to enhance estimation in a robust control perspective. The Ginzburg-Landau equation is used as a model problem having a behavior similar than that of fluid flows.

Keywords: control of fluid flows and fluids-structures interactions, Robust control, Output feedback control
Abstract: We address the problem of controlling the unsteady flow separation over an aerofoil, using plasma actuators. Despite the complexity of the dynamics of interest, we show how the problem of controlling flow separation can be formulated as a simple output regulation problem, so that a simple control strategy may be used. A robust multivariable feedback control is designed and tested in a configuration with two actuator/sensor pairs. Accurate numerical simulations of incompressible flows on a pitching NACA 0012 at Reynolds Re=20,000 are performed in order to illustrate the effectiveness of the proposed approach. Robust, fast flow reattachment is achieved, along with both stabilisation and increase/reduction of the lift/drag, respectively. The control system shows good dynamic performances, as the angle of attack is varied. The chosen output can be experimentally measured by appropriate sensors and the extension of the proposed approach to 3D configurations is straightforward.

Keywords: control of fluid flows and fluids-structures interactions, Optimal control theory, Systems with time-delays
Abstract: The present paper tackles the problem of the control of separated flows. More specifically, it aims at designing a model-based optimal feedforward control. The model is first identified as a delayed bilinear model from experimental data using a special identification procedure, for which the precision is compared to other existing results. Then, using the identified model, the optimal feedforward control problem is formulated and solved for the case of a periodic relay control. The theoretical control results are supported with numerical simulations.

Keywords: Robust time-delay systems, Systems with time-delays, control of heat and mass transfer systems
Abstract: In this paper a model for a pilot-scale tubular reactor is developed using aggregated-parameters. The resulting model is a linear-varying system with time-varying delay, with the delay in the state. This model is simulated and compared to the results obtained from experiments performed on a pilot-scale tubular reactor. In order to design a tracking control and considering the characteristics of the resulting model, predictive control techniques are used. A tracking controller using the block control technique is proposed and is applied during simulation, the results are shown.

Keywords: system identification and adaptive control of distributed parameter systems, model reduction of distributed parameter systems, control of fluid flows and fluids-structures interactions
Abstract: In this study an online adaption of reduced order models (ROM) for fluid flows is presented. Often ROMs are stabilized and tuned by use of an eddy viscosity, which is identified in the offline phase. As novelty the authors estimate the eddy viscosity in the online phase by treating the viscosity as an uncertain parameter in the framework of an extended joint Kalman filter. The mode dependency of the eddy viscosity is estimated at the same time as the eddy viscosity itself using a generalization of typical models for the eddy viscosity of fluid flows. Effectiveness of the proposed method is shown using the Burgers Equation and the incompressible two dimensional Navier-Stokes-Equations.

Keywords: Discrete event modeling and simulation
Abstract: This paper proposes a method to formally check whether formal properties hold on a dynamic model which has been designed by experts for Model Based Safety Analysis/Assessment. As repairable and reconfigurable systems are considered, this model is assumed to be described in the Generalized Boolean-logic Driven Markov Processes (GBDMP) modelling framework. Translation rules are given to obtain a formal model that describes correctly the evolution of the initial model with the semantics of the verification tool. The approach is exemplified on a simple case of standby redundancy.

Keywords: Simulation of stochastic systems, Discrete event modeling and simulation
Abstract: In this article, we present a safety analysis of the case study ``Landing Gear'' proposed recently by Bonniol and Wiels. This case study mixes both physical (hardware) elements and control (software) elements and is representative of a large class of mechatronics systems. For this analysis, we used AltaRica 3.0 as modeling language and stochastic simulation as analysis tool. This experience sketches a methodology to assess the effects of hazards, failures and uncertainties in mechatronics systems.

Keywords: Discrete event modeling and simulation, Diagnosis of discrete event and hybrid systems, Supervisory control and automata
Abstract: Mobile automated systems, such as robots or machinery for precision agriculture, may be designed to perform actions that vary in space according to information from sensors or to a mission map. To be reliable, the design process of such systems should involve the combined verification of spatial and dynamic properties. We consider here CTL model-checking of a mobile robot's behavior, using the UppAal Timed Automata verifier. We consider reachability properties including path finding. Space is modeled as a 2D grid and the mobile robot path is unknown a priori. In this case, the exhaustive state space exploration of model-checking leads to the generation of many possible movements. This exposes such model-checking to combinatorial issues depending on the grid size and the complexity of system dynamics. In this paper, we propose a decomposition methodology reducing the memory requirements for the verification task. The decomposition is twofold. The grid is decomposed in sub-grids and the model-checking query on the whole grid is decomposed in a set of queries on the sub-grids. A set of test cases and check the validity of the decomposition concept. The decomposition methodology is compared to a simpler method that verifies the reachability property without proceeding to decomposition.

Keywords: Discrete event modeling and simulation, Fault detection and diagnosis
Abstract: Complete conformance testing is a model-based test technique for programmable controllers. It checks whether an implementation conforms to its specications with regard to all possible combinations of input signals, which is useful for small scale and safety critical systems. However, the state space explosion issue limits its application to large scale systems. This paper presents a method for reducing state space in generation of test cases by utilizing not only specication models but also features extracted from plant models. The application on a benchmark case study shows that the number of test cases is reduced signicantly.

Keywords: Petri nets, Coordination of multiple vehicle systems, Supervisory control and automata
Abstract: This paper deals with the conflict avoidance problem of an Automated Guided Vehicles (AGV) system, in a Flexible Manufacturing System (FMS). Regarding the complexity of this kind of problems, it has generated many works to find an optimal strategy for scheduling and routing AGVs. In this paper, we propose a new strategy based on a temporal logic, modelled using time Petri nets. It consists in imposing suitable delays on an AGV in order to avoid a critical situation with another AGV. We built an algorithm including three main stages. In the first one, we test the evolution of our system. In the second stage, we calculate our suitable delay, if it exists, by testing the different critical scenario cases. In the last stage, we assign the delays and update the system. The validity of the algorithm is proven mathematically, and its feasibility is shown using a simulation.

Keywords: Supervisory control and automata, Petri nets, Discrete event modeling and simulation
Abstract: In this paper a method to recognize the set of consistent markings in labelled Petri nets is proposed. In this method, the set of unobservable transitions are partitioned into pseudo-observable and strictly unobservable ones, and the subnet induced by the latter is acyclic. The unobservable reach of a marking can be characterized by the union of the strictly unobservable reach of several basis markings, called representative markings, in the unobservable subnet. The set of consistent markings can be characterized by a linear algebraic system based on those representative markings. Based on the representative marking graph, the current marking estimation problem for a labelled Petri net can be efficiently solved. This method does not require the assumption that the unobservable subnet is acyclic.

Keywords: Marine system navigation, guidance and control, Mechanical design of autonomous vehicles, Autonomous underwater vehicles
Abstract: In this paper, we present a bioinpired underwater snake robot (USR) equipped with a passive caudal (tail) fin. In particular, a highly flexible configuration of a USR is presented, which is capable of locomotion both on ground and underwater due to the robust mechanical and modular designs where additional effectors can be attached at different modules of the robot depending on the requirements of the application. This gives flexibility to the operator, who can thus choose the proper configuration depending on the task to be performed in various uncertain environments on ground and underwater. Experimental results for straight line path following control are obtained for a physical USR, that enable a comparison of the USR motion with and without the passive caudal fin, both for lateral undulation and eel-like motion patterns. The experimental results show that a path following control approach which has previously been proposed for USRs without tail fin, can be directly applied to solve the path following control problem of this bioinspired USR with a passive caudal fin. In particular, it is shown that the path following control approach successfully steers the robot towards and along the desired path, and furthermore the results show that it is possible to almost double the forward velocity of the robot by using a passive caudal fin.

Keywords: Autonomous underwater vehicles, Robot Navigation, Programming and Vision, Man-machine interfaces
Abstract: Field experiments in underwater robotics research require a big amount of resources to be able to test the system in sea conditions. Moreover, sea conditions are constantly changing making impossible to reproduce specific situations. For this reasons, testing, comparing and evaluating different algorithms in similar conditions is an utopic situation. In order to deal with this, a framework that mixes real experiments and a simulated environment is proposed to allow objective comparison of algorithms in an scenario as close as possible to field experiments. This is possible using real sensors in a controllable environment, for instance a water tank, adding simulated hostile conditions difficult to reproduce in a controlled environment such as water turbidity, composing a Hardware In the Loop (HIL) framework. This framework is formed by UWSim, an underwater simulator, and a benchmarking module able to measure the performance of external software. This setup is used in a search and recovery use case to compare different tracking algorithms predicting the effect of water turbidity in them. The results allow to choose the best option without the need of dealing with field experiments.

Keywords: Autonomous underwater vehicles, Adaptive and robust control in marine system, Dynamic positioning
Abstract: In various interaction tasks using Underwater Vehicle Manipulator Systems (UVMSs) (e.g. sampling of the sea organisms, underwater welding), important factors such as: i) uncertainties and complexity of UVMS dynamic model ii) external disturbances (e.g. sea currents and waves) iii) imperfection and noises of measuring sensors iv) steady state performance as well as v) inferior overshoot of interaction force error, should be addressed during the force control design. Motivated by the above factors, this paper presents a model-free control protocol for force controlling of an Underwater Vehicle Manipulator System which is in contact with an unknown compliant environment, without incorporating any knowledge of the UVMS's dynamic model, exogenous disturbances and sensor's noise model. Moreover, the transient and steady state response as well as reduction of overshooting force error are solely determined by certain designer-specified performance functions and are fully decoupled by the UVMS's dynamic model, the control gain selection, as well as the initial conditions. Finally, a simulation study clarifies the proposed method and verifies its efficiency.

Keywords: Unmanned marine vehicles, Autonomous underwater vehicles, Mechanical design of autonomous vehicles
Abstract: This work describes the new Unmanned Marine Vehicle e-URoPe developed by CNR-ISSIA. This Remotely Operated Vehicle is realized using the most innovative technical capabilities in order to achieve a flexible structure, adequate to withstand external impacts. The peculiar characteristics of the vehicle, on which is based the design concept, are: easiness of construction, facility of re-configuration and flexibility. Furthermore the vehicle could be completely modified without big efforts in terms of money and time. The vehicle can be equipped with different types of sensors in order to make it flexible and adaptable to various applications such as sampling of water or objects, underwater manipulation, cooperation with underwater operators or with other underwater vehicles, mapping of underwater ground and detection of vegetation lying on the seabed.

Keywords: Sensors and actuators, Autonomous underwater vehicles, Control architectures in marine systems
Abstract: In this paper, a three-finger underwater gripper with force/torque sensor integrated in the wrist interface is presented. The actuation is based on electric servo motors and cable transmission. The gripper is characterized by 8 Degrees of Freedom (DOFs) actuated by only three motors. The coupling among the DOFs of the fingers is implemented by means of multiple pulleys connected to the motor output shaft. The solutions adopted to make the system at the same time simple enough and suitable for marine applications are discussed and analyzed along with the integration of the sensors needed for handling complex manipulation and cooperation tasks. The effectiveness of the device is tested in a pool where the gripper is part of a complex robotic system composed of an Autonomous Underwater Vehicle (AUV) and a dexterous 7-DOFs arm. The goal of the benchmark experiments is the autonomous search of a known object and its recovery and transportation.

Keywords: Mobile robots, Autonomous robotic systems, field robotics
Abstract: This paper presents the development progress of DORIS, an autonomous rail-guided robot designed for inspection and monitoring of Oil and Gas (O&G) facilities. The robot functionalities, electromechanical design, lightweight manipulator, and software architecture are presented, along with possible future tasks and system expansions. The system was first tested in a laboratory environment to validate its concepts and, then, field tests in an industrial plant demonstrated some of its functionalities. DORIS was able to fully navigate on the 3D rail by teleoperation via Wi-Fi, map the environment with a laser scanner, and autonomously detect video and audio anomalies. For the next phase of development, the robot must operate within offshore facilities and classified areas, so that protection standards against explosion and ingress of water and dust must be complied, as shown in a preliminar certification assessment.

Keywords: Knowledge-based control, Fuzzy and neural systems relevant to control and identification, Evolutionary algorithms in control and identification
Abstract: The paper deals with the development of a new control design methodology for nonlinear systems with multiple inputs, based on the hybrid approach using fuzzy logic and genetic algorithms. The proposed hybrid control methodology based on adaptive switching uses the principle of control parameters adaptation for all operating points of a nonlinear system. The control strategy is realized by a fuzzy controller and parameter optimization for different operating points using a genetic algorithm. Theoretical results are verified on a case study dealing with control design for a nonlinear physical model.

Keywords: Fuzzy and neural systems relevant to control and identification, Evolutionary algorithms in control and identification
Abstract: The performance of data-driven models such as Artificial Neural Networks and Support Vector Machines relies to a good extent on selecting proper data throughout the design phase. This paper addresses a comparison of four unsupervised data selection methods including random, convex hull based, entropy based and a hybrid data selection method. These methods were evaluated on eight benchmarks in classification and regression problems. For classification, Support Vector Machines were used, while for the regression problems, Multi-Layer Perceptrons were employed. Additionally, for each problem type, a non-dominated set of Radial Basis Functions Neural Networks were designed, benefiting from a Multi Objective Genetic Algorithm. The simulation results showed that the convex hull based method and the hybrid method involving convex hull and entropy, obtain better performance than the other methods, and that MOGA designed RBFNNs always perform better than the other models.

Keywords: Remote and distributed control, Remote sensor data acquisition, Embedded computer architectures
Abstract: Nowadays ROS (Robot Operating System) based platforms have been widely used in state of art robot researches because of providing reliable mechanisms for fast robot development and algorithm reuse. Among them, modular robots are presented as a Distributed Control System (DCS), in which the data supply and the flow rates must be ensured to guarantee a proper execution. Although ROS network architecture provides a solution for distributed communication, it entails some disadvantages. Real-time constraints assurance and large networks management are some of the main problems. Therefore, this works introduces a ROS-compatible solution for Smart Resource services decoupling on modular robots. Smart Resources are defined as cyber-physical systems that provide high-level operation services. The design and analysis of a new distributed communication architecture for accessing Smart Resource services is addressed along this document. This architecture is called ROS Multi-Peer Architecture (RMPA) and features real-time communication, fully decoupled ROS device execution, and device discovery. So, the integration of RMPA in ROS based developments provides real-time access to the high-level supplied by the Smart Resources. This integration promotes the development of ROS-compatible robot modules based on the Smart Resource design. Next, a set of tests is presented to compare RMPA and ROS communication performance. Moreover, a detailed study of the RMPA performance is also addressed. Finally, as a result of these experiments main advantages and withdrawals of this solution are discussed leading to the establishment of future work and enhancements.

Keywords: Tele-maintenance, Tele-robotics, Internet of things
Abstract: This paper puts a finer point to remote telemaintenance with asynchronous access to an industrial production plant and its data. At first, the condition monitoring records the data from the industrial manipulator and transfers it via the Internet to an application. One possible applications for this data, which can run remotely in order to analyze and to optimize the plant and its processes is a complex sensor view with video integration of one plant cycle (application "FADAT" Facility Asynchronous Data Analysis Tool). Research focus of this paper lies on the user side: The goal of this work is to provide the external expert with a better understanding of the plant and its processes. This is realized for the first time in the examined work environment.

Keywords: Logical design, physical design, and implementation of embedded computer systems, Embedded computer architectures
Abstract: The paper describes in detail the design and implementation of the attitude control system of a small satellite, focusing on the hardware and software aspects. A new control algorithm has been used in order to deal with particular requirements of the system, which are related to its communication, power generation, and thermal control needs. The system is implemented on an embedded on-board computer, and the software has been developed with a model-driven approach using state-of-the-art software tools. Simulation tools have been used for software testing and validation in an integrated validation facility.

Keywords: Logical design, physical design, and implementation of embedded computer systems, Embedded computer architectures, Embedded computer control systems and applications
Abstract: Hard real-time systems are embedded systems with a strong emphasis on the guaranty of safety-critical properties. In order to provide the necessary confidence level, with regard to the respect of functional and non-functional properties, a system analysis that accounts for all possible execution paths must be performed. Symbolic execution has been successfully used to explore and analyze reachable system states. In this paper, we formally define a symbolic execution semantics for an abstract state machine based model. The unification of the update semantics redefined in terms of symbolic moves, enable us to achieve reacher methods for path condition resolution and ultimately better scalability of the execution. The goal of this paper is to provide a formal ground for the integration of symbolic execution in existing timing analysis framworks based on abstract state machines that will facilitate the computability of the analysis tools.

Keywords: Nonlinear process control, Process modeling and identification, Model predictive and optimization-based control
Abstract: Implementation of a liquid cooling transforms a refrigeration system into a combined cooling and heating system. Reclaimed heat can be used for building heating purposes or can be sold. Carbon dioxide based refrigeration systems are considered to have a particularly high potential for becoming efficient heat energy producers. In this paper, a CO_2 system that operates in the subcritical region is examined. The modelling approach is presented, and used for operation optimisation by way of non-linear model predictive control techniques. Assuming that the heat is sold, it turns out that the system has negative operational cost. Depending on the choice of objective function daily revenue varies from about 7.9, [eur] to 11.9, [eur].

Keywords: Control of distributed systems, Nonlinear process control, Advanced control technology
Abstract: This paper presents a distributed non-convex optimization algorithm for solving stochastic optimal control problems to local optimality. Here, our focus is on a class of methods that approximates the probability distribution of the states of a stochastic optimal control problem with uncertain parameters by using a sigma point approach. This leads to a large but structured optimal control problem comprising a number of carefully selected uncertainty scenarios in order to enforce chance constraints. The approach achieves accuracies that are equivalent to a third order moment expansion. However, as the resulting large but structured optimal control problem is challenging to solve with existing numerical tools, this paper proposes a tailored distributed algorithm that exploits the particular structure that arises when applying the sigma point approach. The method is based on a tailored variant of the recently proposed augmented Lagrangian based alternating direction inexact Newton (ALADIN) algorithm. The approach is illustrated by the application to a benchmark case study involving a predator-prey-fishing model.

Keywords: Real time optimization and control, Process optimisation, Process modeling and identification
Abstract: Iterative Real-Time Optimization (RTO) has gained increasing attention in the context of model-based optimization of the operating points of chemical plants in the presence of plant-model mismatch. In all iterative RTO schemes, it is necessary to wait until the plant has reached a steady-state to obtain the required information on plant performance and constraint satisfaction which leads to slow convergence in the case of processes with slow dynamics. It has recently been proposed to use a linear black-box model that is identified online to predict the steady-state values of the plant during the transient between different stationary operating points; these values are then employed in the modifier adaptation with quadratic approximation to drive the process to its optimum. In this contribution, this idea is extended by integrating nonlinear system identification into iterative RTO. Specifically, a Nonlinear Output Error (NOE) model is proposed to describe the dynamics of the process, thus providing a faster prediction of the steady-state of the plant. A robust scheme for the estimation of the model parameters is proposed. The performance of the strategy is illustrated by simulation studies of a continuous stirred-tank reactor. By means of the proposed methodology a fast convergence to the plant optimum can be achieved despite plant-model mismatches

Keywords: Real time optimization and control, Control of large-scale systems, Process optimisation
Abstract: Model-based dynamic optimization of the water-flooding process in oil reservoirs is a computationally complex problem and suffers from high levels of uncertainty. A traditional way of quantifying uncertainty in robust water-flooding optimization is by considering an ensemble of uncertain model realizations. These models are generally not validated with data and the resulting robust optimization strategies are mostly offline or open-loop. The main focus of this work is to develop an adaptive or online robust optimization scheme using residual analysis as a major ingredient. The models in an ensemble are confronted with data and an adapted ensemble is formed with only those models that are not invalidated. As a next step, the robust optimization is again performed (i.e., updated/adjusted) with this adapted ensemble. The adapted ensemble gives a less conservative description of uncertainty and also reduces the high computational cost involved in robust optimization. Simulation example shows that an increase in the objective function value with a reduction of uncertainty on these values is obtained with the developed adaptive robust scheme compared to an open-loop offline robust strategy with the full ensemble and a adaptive scheme using Ensemble Kalman Filter (EnKF), which is one of the most common parameter estimation methods in reservoir simulations.

Keywords: Model predictive and optimization-based control, Optimal operation and control of power systems
Abstract: AC/DC Hybrid Microgrid is the main trend of microgrids. Efficient energy management and optimization is not only the primary means of ensuring the economic operation of microgrid but also the key of the realization of “Plug–and-Play”. Aiming at this problem, this paper proposed an optimization strategy for hybrid microgrid with energy storage and controllable micro-source which is based on distributed Predictive Control (MPC). The proposed algorithm is composed of several MPCs which are distributed in every generators and operate parallel. Power balance constraint and voltage amplitude constraints are designed to coordinate each individual MPC controller for balancing power supply and demand, and ensuring the power quality, respectively. The perturbation of renewable energy is suppressed by state feedback and receding horizon optimizing. In addition, the power loss of the connection converter is also taken into account, which is different from other types of microgrids. Finally, the simulation results show the effectiveness of the proposed method.

Keywords: Real time optimization and control, Control system design, Advanced control technology
Abstract: This paper presents the results of the development of a modular open source platform for experimental control setups. This platform emerged from research on the automatic rotation start-up and landing of a tethered airplane for wind energy harvesting, implementing and testing promising theoretical concepts such as real-time moving horizon estimation (MHE) and non-linear model predictive control (NMPC) on hardware developed in parallel. As experimental setups for testing new control algorithms tend to be fine-tuned by trial and error methods, a rapid control prototyping system for fast evaluation had to be implemented. Technical results of this research are presented in the form of a modular platform for real-time control. The created platform provides a complete toolchain for performing, observing and evaluating control experiments. It offers modular low-cost hardware and free software especially suited for flight control experiments. Clearly defined interfaces between the components allow for expanding on its current capabilities for other control scenarios in need of fast and reliable real-time control. The provided modularity allows for spatial separation of high performance computing hardware from low-level components, permits rapid reconfiguration of the experiment and eases the collaboration and workflow between hardware developers and control engineers.

Keywords: Identification and modelling, Advanced process control, Process optimisation
Abstract: In this paper, a mathematical deflection model of a leveler for cold heavy plates is presented. The model calculates the work roll profile and the leveling forces for a given plate and adjustment of the leveler. The force-deflection relations of the machine model are combined with a nonlinear plate model and solved for the unknown displacements of the work rolls. The plate model is based on a leveling model found in literature. The analytical solution of this model ensures a short computation time. Therefore, the model is suitable for feedforward control and optimization. Finally, the model serves as a basis for calculating the optimal adjustment of the leveler subject to force constraints, which avoids overloading of the machine.

Keywords: Advanced process control, Process optimisation, Real time optimization and control
Abstract: A model-based predictive approach is proposed for the strip head motion control during the steel strip infeed in hot rolling finishing mills. The design is based on a nonlinear simplified mathematical model in a form of ordinary differential equations. It is already shown that this model captures the behavior of FEM models for the strip and the roll gap in an excellent manner. Then the simplified time variant linear model is considered and the discrete-time model is derived in a straightforward manner. In addition the property of flatness is exploited to derive an efficient formulation for the optimization problems. We develop an optimal controller based on a linear programming and compare it with standard quadratic programming. It is shown that the proposed linear program is both more efficient than the quadratic program and the performance is equivalent. Therefore, the linear approach is convenient for the real-time application even without high performance computers. The proposed controller is tested in a co-simulation environment using FEM element model for the strip integrated in Hotint together with a highly nonlinear roll gap model. The simulation results show the excellent accordance of the controlled infeed process for both models (ODE and FEM), as well as the high performance of the closed loop.

Keywords: Advanced process control
Abstract: This paper presents a feedforward control concept for lateral asymmetries in heavy-plate hot rolling. A lateral off-center plate position generally entails asymmetric rolling forces, asymmetric mill stretch, and thus a wedge-shaped exit thickness that may cause a cambered plate contour and a rotatory motion of the plate. In this paper, a model of the mill stand and of the plate movement is presented. The model demonstrates that the plate movement in the reversing mill can be unstable and may cause the plate to collide with the mill housing in the worst case. The developed control concept makes use of the measurement of the shape and the position of the plate by an infrared camera. The controller compensates asymmetric deflections of the two sides of the mill stand associated with laterally asymmetric rolling forces caused by an off-centered plate position. Both simulations and long-term operation results at an industrial rolling mill confirm the robustness of the proposed control concept and show an improvement of the accuracy of the plate contour.

Keywords: Monitoring of product quality and control performance, Process observation and parameter estimation
Abstract: This paper presents a novel approach to monitor control performance of nonlinear processes that can be described as state-dependent models (SDMs). A discrete Kalman filter (KF) is established to estimate the SDM parameters. A covariance control formulation is introduced to split the system closed-loop variance/covariance into two terms, one term to account for the minimum expected quadratic loss bound (equivalent to the minimum variance performance bound but in state space formulation), and another to account for performance deviations from the minimum variance bound. Simulation studies have been conducted on several nonlinear process systems including a cold rolling mill model with roll eccentricity and a steel making system with real time oxyfuel slab reheating furnace control data. The case study results demonstrate the computational efficiency of the proposed strategy in real time monitoring and control of systems with fast, nonlinear and time-varying dynamics.

Keywords: Monitoring of product quality and control performance, Identification and modelling, Data mining and multivariate statistics
Abstract: Modern steel rolling process is commonly designed to produce products with a variety of grade specifications. There exist enormous historical data for the typical products in large batch production; while for small-batch customized products, the lack of sufficient historical data may prevent successful application of traditional data-based process modeling and quality prediction methods. In this paper, a practical and effective strategy is developed for fast modeling and flatness defect prediction of a steel rolling process. The key idea is based on model migration, assuming that high-performance quality prediction models (defined as Base Models) have been available for the typical products. A Principal Component Analysis (PCA) similarity indicator is adopted to measure the difference between new operating modes and the typical operating modes, based on which, new operating modes are divided into non-significantly-changed modes and significantly-changed modes. For the former, the new flatness defect prediction model is developed by screening the similar data in the typical modes and augmenting them into the modeling data set for the new mode. For the latter, the new model is obtained by reconstructing the base model via parameters’ shifting and scaling. Case study results can show the validity of the proposed method.

Keywords: Advanced process control, Identification and modelling
Abstract: The control of the curvature and the contact force at the strip-roll contact point of a metal strip in an experimental device is investigated. For this purpose, a material model and a steady state strip deformation model are derived. Using these models, feasible combinations of curvature and contact force are computed. A control structure is proposed that comprises a feedforward and a feedback part. Exponential stability of the closed-loop system is shown. Results from a numerical example verify the robustness of the controller against model-plant mismatches and its suitability for disturbance rejection.

Keywords: Robustness analysis, Model following control, Parametric optimization
Abstract: The paper discusses the robustness a model predictive control (MPC). Different MPC tuning methods are proposed in order to obtain the desired closed-loop behavior. Both cases when the anticipation is and is not taken into account are treated. An application to the steering wheel position control is provided. The obtained MPC allows to obtain a robust control and to take into account a future reference trajectory. Potential difficulties of such an approach are discussed as well.

Keywords: Robust linear matrix inequalities, Robust controller synthesis, Convex optimization
Abstract: Constraints on control inputs and system outputs are usually given in the non-symmetric form. However, various robust MPC design approaches based on LMIs consider the symmetric representation of the constraints. The aim of the paper is to present a novel concept to overcome this limitation. The approach introduces a time-varying vector of symmetric constraints. Its entries are determined using a switching indicator function. The main advantage is the same computational burden of the solved optimization problem compared to the original procedure. Closed-loop stability is guaranteed either by the feasibility of the modified optimization problem or by a pre-designed support controller when the optimization problem is infeasible. An illustrative example demonstrates that the control performance is significantly improved using the developed strategy.

Keywords: Robust linear matrix inequalities, Output feedback control, Uncertainty descriptions
Abstract: The aim of this paper is to investigate the problems of H-infinity and H-2 dynamic output feedback control for continuous-time Markov jump linear systems (MJLS) subject to uncertain transition rates. Synthesis conditions are proposed in terms of parameter-dependent matrix inequalities with a scalar parameter and polynomial variables. The conditions become linear for fixed values of the scalar parameter, which provides an extra degree of freedom to search for feasible solutions and less conservative H-infinity and H-2 bounds. Differently from the existing approaches, the proposed method provides full order mode-dependent controllers constructed in terms of the state space matrices of the operation modes and partitions of the slack variables introduced in the design conditions. Therefore, the resulting controller does not depend explicitly on the Lyapunov matrix, being robust with respect to the uncertain transition rates. Moreover, the closed-loop MJLS stability and the bounds to the H-infinty or H-2 norm are certified by means of polynomially parameter-dependent Lyapunov matrices. Numerical examples illustrate the applicability and the advantages of the proposed technique when compared with other approaches from the literature.

Keywords: Linear parameter-varying systems, Robust linear matrix inequalities, Lyapunov methods
Abstract: This paper deals with observer-based stabilization for a class of Linear Parameter-Varying~(LPV) systems in discrete-time case. A new LMI design method is proposed to design the observer-based controller gains. The main contribution consists in providing a new and convenient way to use the congruence principle to reduce the conservatism of some existing results in the literature. This use of congruence principle leads to some additional slack matrices as decision variables, which make disappear some bilinear terms. To the authors' best knowledge, this is the first time the congruence principle is exploited in this way. The effectiveness and superiority of the proposed design techniques, compared to existing results in the literature, are demonstrated through two numerical examples.

Keywords: Linear parameter-varying systems, Lyapunov methods, Robust control
Abstract: In the paper a new robust guaranteed cost output-feedback gain-scheduled PID controller design technique is presented for affine linear parameter-varying systems under polytopic model uncertainty, with the assumption that the scheduled parameters are affected with absolute uncertainty. The proposed centralized or decentralized method is based on the Bellman-Lyapunov equation, guaranteed cost, and parameter-dependent quadratic stability. The robust stability and performance conditions are translated to an optimization problem subject to bilinear matrix inequalities, which can be solved or further linearized. As the main result, the suggested stability and performance conditions without any restrictions on the controller structure are convex functions of the scheduling and uncertainty parameters. Hence, there is no need for applying multi-convexity or other relaxation techniques and consequently the proposed solution delivers a less conservative design method. The viability of the novel design technique is demonstrated and evaluated through numerical examples.

Keywords: Robust control applications, Tracking, Disturbance rejection
Abstract: In this work we propose a robust controller to do tracking using the sub-optimal H_infinity technique with the approach of differential game theory. The problem is solved in two steps using the Block Control technique. The controller is designed in discrete time and it is synthesized for electromechanical systems which are modeled by means of the Euler-Lagrange formulation. Making use of the discrete Hamilton-Jacobi-Isaacs equation and the discrete Riccati equation the control law is derived. The control law is then applied to a continuous-time 6-DOF bipedal robot model in order to track the walking pattern references for each link. The system along with the control law is simulated, where the system is subjected to a disturbance that emulates the action of a group of external unknown bounded forces over the links of the bipedal robot. The simulation results are shown displaying robustness against the disturbance, torques required from the motors are plot and since the control input was optimized the values lie within a reasonable bound. Furthermore, this work is compared to a similar approach that uses H_infinity technique in continuous time.

Keywords: Robust control applications, Linear parameter-varying systems, Robust linear matrix inequalities
Abstract: In this paper, a robust Linear Quadratic Regulator (LQR) of a NACA 0018 wing with a flap actuator is developed for stall flutter suppression. The nonlinear and switched set of equations of the aeroelastic model is detailed and conveniently expressed as a polytopic uncertain system. A Linear Matrix Inequalities (LMIs) formulation of the LQR problem in the presence of uncertainties is used for the control design. Simulation results confirm the desirable behavior of the arising closed-loop system.

Keywords: Linear parameter-varying systems, Robust controller synthesis
Abstract: Gain scheduling controller design scheme employing piecewise affine (PWA) model for nonlinear controlled plant is given in the paper. Recent result of (Ilka et al., 2016) is further developed for the presented PWA model based on identification in working points. The PWA model is structured in such a way which reduces computational complexity of the corresponding gain scheduling control design scheme. The proposed modelling and control approach is illustrated on a case study: drum boiler nonlinear simulation model presented as a benchmark example in (Morilla, 2012). The number and choice of working points and their influence on performance of the respective gain scheduling control loop is discussed as well.

Keywords: Robust linear matrix inequalities, Robust control applications, Robust control
Abstract: The paper presents soft-constrained alternative robust (SCAR) MPC applied to a laboratory heat exchanger. Robust MPC is designed using a novel alternative strategy that combines suitable properties of existing approaches, namely, methods based on nominal system optimization and additional control input saturation. LMI-based robust MPC is supplemented by soft constraints and a new module SOFT-CON in MATLAB/Simulink toolbox MUP is developed. The proposed robust MPC strategy is validated in laboratory conditions. The experimental results confirm improved control performance of a heat exchanger subject to the soft-constraints and energy savings in comparison with existing approaches.

Keywords: Linear parameter-varying systems, Switching stability and control, Robust controller synthesis
Abstract: The paper deals with design and simulation of hierarchical multi-loops feedback magnetic plasma control system on the base of experimental data for operating Globus-M spherical tokamak in line with the special methodology developed. The components of the system are designed to achieve high-performance operation during short pulses of plasma discharges about 200 ms. The plasma equilibrium reconstruction algorithm with regularization in terms of moving filaments without iterations was developed. The Linear Parameter Varying plant model was derived from reconstructed plasma equilibriums as a distributed parameter system with time-varying parameters. A switching plasma shape multivariable controller was designed by the robust loop-shaping approach for magnetic field at X-point and poloidal fluxes on plasma separatrix (isoflux control). The novelty of the plasma shape control system is the application of robust switching control with a controller state vector matching. The feedback control was applied to the whole discharge with the transition from a limiter phase to a diverter phase when the plasma changed its magnetic topology as a controlled structure.

Keywords: Linear parameter-varying systems, Robust linear matrix inequalities, Observers for linear systems
Abstract: This paper addresses the problem of gain-scheduled filter design with guaranteed H-2 performance for linear parameter-varying discrete-time systems with arbitrarily fast time-varying parameters. The filters to be designed have order greater than the order of the system being filtered. The design procedure is formulated in terms of Linear Matrix Inequalities. As is well known, gain-scheduled filters can provide superior performance for linear parameter-varying systems when compared with robust filters. The proposed non-minimal order H-2 gain-scheduled filtering strategy can further improve the results by enlarging the structure of the filter. Examples illustrate the results, showing that larger order filters can have improved performance, providing lower guaranteed H-2 costs when compared with other approaches based on full order filtering from the literature.

Keywords: Linear parameter-varying systems
Abstract: Although kernel methods have been succesfully applied to many different problems in system identification, choosing an optimal kernel structure can be challenging - particularly in higher- order problems. However by noting that structural information, such as linearity, separability and smoothness, is contained in the functional derivatives, it can be seen that the kernel selection problem can be reduced to a simpler regularisation problem over specified derivatives.

In this vein, here a novel approach to the control of smoothness in nonparametric LPV identification is proposed. By constraining the derivatives of the scheduling dependencies through a regularisation term, the model smoothness can be linearly controlled through the regularisation hyperparameter, without needing to optimise over the kernel function.

A simulation example is presented to show how different structural hypotheses can be tested at minimal extra cost to the user, with the proposed approaches validated against a method from the literature.

Keywords: Robust control applications, backstepping control of distributed parameter systems
Abstract: In this paper, a novel robust control strategy named uncertainty and disturbance estimator (UDE) is applied to the stabilization of an unstable heat equation with Dirichlet type boundary actuator and unknown time-varying input disturbance. The system is stabilized by the backstepping approach and the unknown input disturbance is compensated by the UDE-based method which constructs an estimation of the disturbance through filtering the system input U(t) and boundary state u(1, t). Compared to other existing disturbance compensation methods, the UDE-based method only requires the spectrum information of the disturbance signal. Furthermore, the output feedback version of the proposed control is also derived for the practical implementation purpose. Stability analysis of the closed-loop system for both state feedback and output feedback cases are carried out and simulation examples are also provided to verify the proposed method.

Keywords: Linear parameter-varying systems, Distributed robust controller synthesis
Abstract: This paper considers the controller design problem for parameter-varying distributed systems, whose time/space-varying dynamics can be characterized by temporal/spatial linear parameter-varying (LPV) models defined at the spatially-discretized subsystems. Assuming a rational functional dependence on the scheduling parameters, the distributed LPV model in linear fractional transformation (LFT) form renders analysis and synthesis conditions at the subsystems level with the application of Finsler's lemma and the full block S-procedure technique. The designed distributed controller inherits the interconnected structure of the plant and has a (predefined) fixed structure. Simulation results using a spatially-varying heat equation demonstrate the satisfactory performance of the proposed control design method.

Keywords: Flying robots, Autonomous robotic systems, Guidance navigation and control
Abstract: New applications for aerial vehicles are emerging recently. They imply the interaction with the environment with the possibility to modify it. In this paper, a control scheme to catch a ball falling using a quadcopter is conceived. The control goal is to design a controller that ensures the quick convergence in the dynamics of the quadcopter in order to catch the ball before that it touches the ground. The algorithm is based on the sliding mode approach to assure robustness and finite time convergence. The parabolic motion is studied to obtain the ball trajectory and computes the capture limit time. Simulation results verifies the well performance of the controller to catch the ball even in presence of unknown and external disturbances.

Keywords: Telerobotics, Networked robotic system modeling and control, telepresence
Abstract: Teleoperation is an important technology in many high risk and challenging applications. However model uncertainty and unknown and time-varying communication delay can make the system unstable or badly affects its usability if not properly managed. In this paper we exploit the well-known Smith predictor to improve the performance. To take advantages of the Smith predictor, we have to guarantee that the round-trip time of the bilateral teleoperation system is constant and known. To reach this goal we introduce adaptive buffers at the master and slave side to compensate for the delay jitter, to estimate lost packets and to filter out the noise; at the same time the adaptation mechanism allows to change the size of the buffers to use the smallest size according to the actual network conditions. Experimental results on a one-degree of freedom teleoperated system show the effectiveness of the proposed approach.

Keywords: Mobile robots, Autonomous robotic systems, Guidance navigation and control
Abstract: This paper presents a novel approach to the source seeking problem, where a group of mobile agents tries to locate the maximum of a scalar field defined on the space in which they are moving. The agents know their position and the local value of the field, and by communicating with their neighbors estimate the gradient direction of the field. A distributed cooperative control scheme is then designed that drives the group towards the maximum while maintaining a specified formation. Previously proposed control schemes that are based on a combination of H_infty-optimal formation control and local gradient estimation suffer from premature convergence to local maxima. To overcome this problem, here the use of particle swarm optimization for locating the global maximum is proposed. Agents take the role of particles and an information flow filter approach is employed to separate the consensus dynamics from the local feedback loops governing the agent dynamics. Stability of the overall scheme is established based on the small gain theorem, and by decomposing the synthesis problem for the distributed information flow filter the problem size is reduced to that of a single agent. Simulation results with multiple maxima and quadrocopter models as agents illustrate the practicality of the approach.