This book presents Networked Control System (NCS) as a particular kind of a real-time distributed system (RTDS), composed of a set of nodes, interconnected by a network, and able to develop a complete control process. It describes important parts of the control process such as sensor and actuator activities, which rely on a real-time operating system, and a real-time communication network. As the use of common bus network architecture introduces different forms of uncertainties between sensors, actuators, and controllers, several approaches such as reconfigurable systems have been developed to tackle this problem. Moreover, modeling NCS is a challenging procedure, since there are several non-linear situations, like local saturations, uncertain time delays, dead-zones, or local situations, it is necessary to deal with. The book describes a novel strategy for modelling and control based on a fuzzy control approach and codesign strategies.

Optimal and Robust Scheduling for Networked Control Systems tackles the problem of integrating system components—controllers, sensors, and actuators—in a networked control system. It is common practice in industry to solve such problems heuristically, because the few theoretical results available are not comprehensive and cannot be readily applied by practitioners. This book offers a solution to the deterministic scheduling problem that is based on rigorous control theoretical tools but also addresses practical implementation issues. Helping to bridge the gap between control theory and computer science, it suggests that the consideration of communication constraints at the design stage will significantly improve the performance of the control system. Technical Results, Design Techniques, and Practical Applications The book brings together well-known measures for robust performance as well as fast stochastic algorithms to assist designers in selecting the best network configuration and guaranteeing the speed of offline optimization. The authors propose a unifying framework for modelling NCSs with time-triggered communication and present technical results. They also introduce design techniques, including for the codesign of a controller and communication sequence and for the robust design of a communication sequence for a given controller. Case studies explore the use of the FlexRay TDMA and time-triggered control area network (CAN) protocols in an automotive control system. Practical Solutions to Your Time-Triggered Communication Problems This unique book develops ready-to-use engineering tools for large-scale control system integration with a focus on robustness and performance. It emphasizes techniques that are directly applicable to time-triggered communication problems in the automotive industry and in avionics, robotics, and automated manufacturing.

The problem of jointly designing a robust controller and an intelligent scheduler for networked control systems (NCSs) is addressed in this thesis. NCSs composing of multiple plants that share a single channel communication network with uncertain time-varying transmission times are modeled as switched polytopic systems with additive norm-bounded uncertainty. Switching is deployed to represent scheduling, the polytopic uncertainty to overapproximatively describe the uncertain time-varying transmission times. Based on the resulting NCS model and a state feedback control law, the control and scheduling codesign problem is then introduced and formulated as a robust (minimax) optimization problem with the objective of minimizing the worst-case value of an associated infinite time-horizon quadratic cost function. Five robust codesign strategies are investigated for tackling the introduced optimization problem, namely: Periodic control and scheduling (PCS), Receding-horizon control and scheduling (RHCS), Implementation-aware control and scheduling (IACS), Event-based control and scheduling (EBCS), Prediction-based control and scheduling (PBCS). All these codesign strategies are determined from LMI optimization problems based on the Lyapunov theory. The properties of each are evaluated and compared in terms of computational complexity and control performance based on simulation and experimental study, showing their effectiveness in improving the performance while utilizing the limited communication resources very efficiently.

This book nds its origin in the WIDE PhD School on Networked Control Systems, which we organized in July 2009 in Siena, Italy. Having gathered experts on all the aspects of networked control systems, it was a small step to go from the summer school to the book, certainly given the enthusiasm of the lecturers at the school. We felt that a book collecting overviewson the important developmentsand open pr- lems in the eld of networked control systems could stimulate and support future research in this appealing area. Given the tremendouscurrentinterests in distributed control exploiting wired and wireless communication networks, the time seemed to be right for the book that lies now in front of you. The goal of the book is to set out the core techniques and tools that are ava- able for the modeling, analysis and design of networked control systems. Roughly speaking, the book consists of three parts. The rst part presents architectures for distributed control systems and models of wired and wireless communication n- works. In particular, in the rst chapter important technological and architectural aspects on distributed control systems are discussed. The second chapter provides insight in the behavior of communication channels in terms of delays, packet loss and information constraints leading to suitable modeling paradigms for commu- cation networks.

Networked Control Systems (NCS) is a growing field of application and calls for the development of integrated approaches requiring multidisciplinary skills in control, real-time computing and communication protocols. This book describes co-design approaches, and establishes the links between the QoC (Quality of Control) and QoS (Quality of Service) of the network and computing resources. The methods and tools described in this book take into account, at design level, various parameters and properties that must be satisfied by systems controlled through a network. Among the important network properties examined are the QoC, the dependability of the system, and the feasibility of the real-time scheduling of tasks and messages. Correct exploitation of these approaches allows for efficient design, diagnosis, and implementation of the NCS. This book will be of great interest to researchers and advanced students in automatic control, real-time computing, and networking domains, and to engineers tasked with development of NCS, as well as those working in related network design and engineering fields.

This book introduces a unique, packet-based co-design control framework for networked control systems. It begins by providing a comprehensive survey of state-of-the-art research on networked control systems, giving readers a general overview of the field. It then verifies the proposed control framework both theoretically and experimentally – the former using multiple control methodologies, and the latter using a unique online test rig for networked control systems. The framework investigates in detail the most common, communication constraints, including network-induced delays, data packet dropout, data packet disorders, and network access constraints, as well as multiple controller design and system analysis tools such as model predictive control, linear matrix inequalities and optimal control. This unique and complete co-design framework greatly benefits researchers, graduate students and engineers in the fields of control theory and engineering.

Optimal Networked Control Systems with MATLAB® discusses optimal controller design in discrete time for networked control systems (NCS). The authors apply several powerful modern control techniques in discrete time to the design of intelligent controllers for such NCS. Detailed derivations, rigorous stability proofs, computer simulation examples, and downloadable MATLAB® codes are included for each case. The book begins by providing background on NCS, networked imperfections, dynamical systems, stability theory, and stochastic optimal adaptive controllers in discrete time for linear and nonlinear systems. It lays the foundation for reinforcement learning-based optimal adaptive controller use for finite and infinite horizons. The text then: Introduces quantization effects for linear and nonlinear NCS, describing the design of stochastic adaptive controllers for a class of linear and nonlinear systems Presents two-player zero-sum game-theoretic formulation for linear systems in input–output form enclosed by a communication network Addresses the stochastic optimal control of nonlinear NCS by using neuro dynamic programming Explores stochastic optimal design for nonlinear two-player zero-sum games under communication constraints Treats an event-sampled distributed NCS to minimize transmission of state and control signals within the feedback loop via the communication network Covers distributed joint optimal network scheduling and control design for wireless NCS, as well as the effect of network protocols on the wireless NCS controller design An ideal reference for graduate students, university researchers, and practicing engineers, Optimal Networked Control Systems with MATLAB® instills a solid understanding of neural network controllers and how to build them.