Output Feedback Controller for Dissipative Networked Control Systems via Markovian Jump System Approach

Driven by recent telecommunication demand, shared communication channels are more abundant today than ever before. These shared wired/wireless networks for communication are being exploited more and more in control systems to connect sensors, controllers and actuators resulting in so-called networked control systems (NCSs). NCSs replace the more traditional control systems where dedicated point-to-point (wired) connections are being used. The advantages of using NCS technology are inexpensive and easily modifiable communication links which allow control algorithms to be easily implemented in situations where dedicated connections are not possible (either economically or physically). However, the drawback is that the control system is susceptible to undesirable (possibly destabilizing) side-effects such as time-varying transmission intervals, time-varying delays, packet dropouts, quantization and a shared communication medium. These network-induced effects undermine fundamental assumptions on which traditional control theory is built and, therefore, it is essential to develop new techniques and tools that can be used to analyze and/or design control systems which communicate via a shared network. This thesis advances NCS analysis and design methodologies by contributing new theoretical developments, new software tools and new experimental validation results. The first new theoretical development is in the area of analyzing robust stability properties with respect to network-induced effects. A sum of squares (SOS) approach for a class of nonlinear NCSs incorporating bounded time-varying delays, bounded time-varying transmission intervals and a shared communication medium is developed. Mathematical models that describe these nonlinear NCSs are cast into suitable hybrid system formulations. Based on these hybrid system formulations, (families of) Lyapunov functions are constructed using SOS techniques. Amongst other benefits, it is shown that this technique improves the guaranteed robustness margins compared to existing work. The second new theoretical development concerns the design of networkaware decentralized controllers guaranteeing robust stability properties with respect to network-induced effects. We develop one of the first approaches based on semidefinite programming techniques to synthesize stabilizing decentralized observer-based output-feedback controllers for linear plants where the controllers, sensors and actuators are connected via a shared communication network subject to time-varying transmission intervals and delays. To effectively deal with the shared communication medium, a switched observer structure is adopted that switches based on the transmitted measured outputs and a switched controller structure is also adopted that switches based on the transmitted control inputs at each transmission time. By taking a discrete-time switched linear system perspective on modeling these decentralized NCSs, we are able to derive a general model that captures all these networked and decentralized control aspects. We provide linear matrix inequality (LMI)-based synthesis conditions which, if satisfied, provide stabilizing observer-based controllers that are both decentralized and robust to network effects. Regarding new software tools, the first prototype of a toolbox is developed to automate (robust) stability analysis (and controller design) for NCSs. Specifically, it is shown that the toolbox can be employed to efficiently verify if a linear time-invariant (LTI) plant and an LTI controller interconnected with a shared network are robust to certain network imperfections. The main intention of the toolbox is to make the available theory readily accessible to and applicable for the general control community. Additionally, the chosen software structure enables the incorporation of custom models or custom stability/performance analysis conditions in an easy manner, thereby allowing the control community to contribute and to further develop the toolbox. Finally, an experimental case study involving a wirelessly controlled inverted pendulum/cart system is investigated. In particular, the communication network itself is analyzed such that the network-induced effects can be characterized in terms of bounds on the transmission intervals and transmission delays. Based on these bounds, the prototype toolbox is applied to analyze the robustness regions for different performance specifications, which aid in tuning the controller to achieve more closed-loop robustness with respect to the network-induced effects. This leads to a validation of the developed theory in an experimental setting. In addition to the validation of the developed theory, many new insights into the network behavior are obtained and explained, thereby raising new interesting questions for future research on NCSs.

This kind of control systems wherein the control loops are closed through a real time communication network can be called networked control systems. Networked control system is a new hot topic in the control engineering. The reduction of bandwidth necessitated by the communication network in a networked control system is a major concern. For this reason, a computation method of reducing the number of data packet exchanges between the sensor and the controller/actuator was explored. A novel model of controller and intelligent prtotocol were also designed for reducing the number of data packet exchanges which could make the networked control system stable.

Design, Analysis and Real-time Implementation of Networked Predictive Control Systems

Connecting a complex control system with various sensors, actuators, and controllers as a networked control system by a shared data network can effectively reduce complicated wiring connections. This system is also easy to install and maintain. The trend is to use networked control systems for time-sensitive applications, such as remote DC motor actuation control. The performance of a networked control system can be improved if the network can guarantee quality-of-service (QoS). Due to time-varying network traffic demands and disturbances, QoS requirements provided by a network may change. In this case, a network has to reallocate its resources and may not be able to provide QoS requirements to a networked control application as needed. Therefore, the application may have to gracefully degrade its performance and perform the task as best as possible with the provided network QoS. This paper proposes a novel approach for networked DC motor control systems using controller gain adaptation to compensate for the changes in QoS requirements. Numerical and experimental simulations, and prototyping, are presented to demonstrate the feasibility of the proposed adaptation scheme to handle network QoS variation in a control loop. The effective results show the promising future of the use of gain adaptation in networked control applications.

Due to major advancements in the area of networking over the past decade, a new paradigm of control systems has emerged, namely networked control systems. Such systems differ from classical control systems in that their control loops are closed around communication networks. Thus, the need for new stability and performance guarantees arises. In this paper, we aim to shed some light on the major advancements and inherent problems in networked control systems.

In this paper, static output feedback stochastic stabilization and disturbance attenuation issues for a class of discrete-time Networked Control Systems (NCSs) subject to random failures and random delays are addressed. The different random processes are modeled as Markovian chains, and the resulting closed-loop system belongs to the class of discrete-time Markovian Jump Linear Systems (MJLS). Results are formulated as matrix inequalities. A numerical algorithm based on nonconvex optimization is provided and its running is illustrated on a classical example from literature.

In this paper, the robust H∞ control problem is developed for a class of linear time-varying networked control system (NCS) with uncertainties and external disturbance. In network, the network-induced delay and packet dropouts are simultaneously considered. Firstly, a discrete-time switched system model is established based on the signals transmission delay in network. Then, a time-varying H∞ controller is designed. Such the controller can vary according to delay in network. Furthermore, by constructing delay-dependent Lyapunov-Krasovskii functional, a sufficient condition is given to guarantee that the closed-loop system is stochastically stable with an H∞ disturbance attenuation level in terms of nonlinear matrix inequalities. In order to solve the controller gain, the cone complementarity linearization (CCL) algorithm is employed. Finally, a networked DC motor control system is analyzed to illustrate the effectiveness of the proposed method.

The problem of forward and backward time delays is significantly important for both control and feedback loop of networked control systems. These time delays give rise to latency in performance and thereby may destabilize the system. Therefore numerous methods have been proposed about time delay identification/estimation and compensation for networked control systems, especially for bilateral teleoperation systems. However, most compensation methods have been accomplished by considering offline time delay estimation for linear/nonlinear time delay control systems. In this work, we propose an observer based estimation algorithm for round trip delay which is the sum of forward and backward time delays for a 1 degree-of-freedom nonlinear bilateral teleoperation system. Via Lyapunov based stability analysis, global boundedness of the observer errors along with their ultimate convergence and the convergence of the round trip delay estimator to the vicinity of its real value can be guaranteed in the closed-loop system. Finally, simulation and experimental studies are carried out utilizing the last link of a PHANToM Omni Haptic device moving like a one-link robot in the vertical plane.

The use of a communication network in a control loop has gained increasing attention in recent years, because it can offer many advantages. One of major challenges in this so-called networked control systems (NCS) is the network-induced delay effect in the control loop. In this paper, a networked control strategy based on generalized predictive control (GPC) is presented, which can compensate for the communication network delays. A stability analysis method for the control strategy is proposed. The simulation results illustrate effectiveness of this method.

In this study, a particle swarm optimization (PSO) based Multi-Agent Reinforcement Learning (MARL) approach for load frequency control (LFC) of multi-area power system over communication network considering communication delay and packet loss is presented. A networked control system (NCS) is framed to model a constant delay and packet loss using Markovian approach. The controller using PSO based MARL technique having two levels of controlled action in each area of power system act as an estimator agent and controller agent respectively. The proposed method for frequency regulation of multi-area power system is studied in detail and verified for different types of load disturbances. In addition, to check the system dynamic performance of electric power system a mean square errors (MSEs) of states with different value of communication delay are computed. The simulation results of this study is validated and compared with some pre-design methods available from literatures, along with capacity of multi agent system (MAS) for application of LFC in power system over communication network.

Markovian jumping systems have arisen naturally in the mathematical modeling of phenomena spanning disciplines in the social sciences, natural sciences, and engineering. This kind of stochastic dynamical systems can be employed to model the dynamics when parameters are subject to random abrupt changes due to sudden environment changes, subsystem switching, system noises, executor faults, and so forth. Much attention has been given to modeling, optimization, and real applications of such stochastic dynamical systems in the literature in recent years. As the advanced control and optimization will provide a basis for the design and application of such stochastic systems, these advanced techniques would result in substantial and sustainable benefits. The accepted papers in this special issue include stochastic stability, stabilization, stochastic control optimization, system modeling and identification methods, predictive control, signal processing, robust filtering, multiagent systems, networked control systems, time-delayed systems, neural networks, the Takagi-Sugeno fuzzy systems, simulated annealing, and fault detection methods.

The problem of stabilization of networked control systems (NCSs) with data packet dropout is studied. Sufficient conditions are presented on the stability and stabilization of the NCSs with packet dropout. The novelty of this work lies in that NCSs with arbitrary but finite data packet dropout are modelled as switched linear systems, and this enables us to apply the result of switched systems to the analysis and synthesis of such NCSs. The admissible upper bound of the dropped packets can be determined by a set of linear matrix inequalities (LMIs) which guarantee the stability of the NCSs. Stabilizing controllers (via state feedback and static output feedback) can be constructed by solving a set of LMIs. Also, for an NCS with a convergence rate constraint, similar results are obtained. Examples are worked out to illustrate the effectiveness of the proposed method

Networked control systems (NCS) consist of sensors, actuators and controllers the operations of which may be distributed over geographically disparate locations and co-ordinated by the exchange of information passed over a communication network. The communication network may be physically wired or not. The widespread applications of the Internet have been a major driving force for research and development of NCS. NCS have advantages in terms of cost reduction, system diagnosis and flexibility, minimizing wiring and making the addition and replacement of individual elements relatively simple; efficient data sharing makes taking globally intelligent control decisions easier with an NCS. The applications of NCS are very wide, from the large scale of factory automation and plant monitoring to the smaller but complicated networks of computers in modern cars, places and autonomous robots. Networked Control Systems presents the most recent results in stability and robustness analysis as well as new developments related to networked fuzzy and optimal control. Many of the chapters contain details of case-studies, experimental, simulation and/or other application-related work showing how the theories put forward can be implemented in real systems. The state-of-the art research reported in this volume by an international team of contributors will make Networked Control Systems an essential reference for researchers and postgraduate students in control, electrical, computer and mechanical engineering and computer science.

We consider two closely related dynamic self-organization problems in networked control systems. Both are forms of dynamic clustering of nodes. The structure of networked control systems is often abstracted using graph theory. In this abstraction, the nodes of the graph represent the agents and the edges between them represent the relation(s) or the possibility of communication between the corresponding agents. The topology of the communication network supporting a networked control system has critical consequences for its performance. The first problem we address is the development of a distributed self-organization algorithm, resulting into a dynamic two level hierarchy of leader and regular agents, which substantially improves the convergence speed of distributed algorithms utilized by the networked control system. For the second problem, we consider the collaborative control of a group of autonomous mobile agents (e.g. vehicles, robots) supported by a mobile wireless network, consisting of many ground and a few aerial nodes. The agents collaborate to achieve a common goal or objective, like to move in a particular area and cover it, while avoiding obstacles and collisions. Building upon our earlier work on deterministic, randomized and hybrid distributed coordination algorithms we consider the communication needs of the agents, and in particular the connectivity of their communication network as they move. We develop distributed algorithms that automatically select some agents and move them appropriately so as to maintain certain degree of desired connectivity among the moving agents. We characterize the trade-off between the gain from maintaining a certain degree of connectivity vs. the combined cost of communications and the associated dynamic re-positioning of agents. We also describe classes of efficient communication topologies and in particular their similarity to dynamic small world topologies and extensions.

Networked control systems (NCSs), in which controllers and actuators are connected by communication networks, have been utilized in both industrial and consumer applications. In addition, sleep-based energy-efficient network interfaces have been developed for constructing a green networked society. The combination of the NCSs and energy-efficient network interfaces is a promising approach to reduce the power consumption of NCSs. However, sleeping of the network interface results in loss of data to be transmitted between a controller and an actuator. The sleep-induced data loss causes degradation of control performance. Moreover, NCSs originally include network delay for both forward and feedback paths, which also degrades control performance. This paper proposes a time-delay and data-loss compensation method using a modified communication disturbance observer (MCDOB) for NCSs with sleep-based energy-efficient interfaces. The proposed MCDOB can simultaneously compensate for not only the network delay but also sleep-induced data loss as a disturbance, whereas a conventional communication disturbance observer (CDOB) considers only network delay or network-induced data loss and cannot be directly introduced into the NCSs with sleep-based energy-efficient interfaces. Experimental results show that the proposed method with MCDOB outperforms the conventional method without the MCDOB in terms of integral square error (ISE) and communication rate, which indicates the power consumption of network interfaces.