Networked control systems (NCS) mark a consummate union of the communication and control disciplines, both of which evolved independently over the past 70-to-80 years. NCS are key enablers for so-called cyber-physical systems (CPS). CPS help us interact with the physical world using digital technology. Typical examples of CPS include energy systems, healthcare systems, and transportation systems, to name a few. To drive home the usage of digital technology in these systems, let us briefly look at transportation systems. In these systems, on-board sensors present on vehicles interact regularly with other vehicles and the deployed infrastructure via wireless networking. This interaction causes the corresponding controllers to take a suitable remedial action. Indeed, this type of feedback-based control is at the heart of applications like collision warning systems. An important difference between the classical (feedback-based) control systems and the NCS is that, in the latter, the feedback is not instantaneous and error free. This is because the communication between the underlying physical system (which is to be controlled) and the controller happens over channels of limited bandwidth, which are subject to ambient noise and interference from other communications. The issue of stability is central and is indeed common to both classical control systems and NCS. The problem of stability in classical control systems is well studied and established, while the study of stability in NCS is relatively new; it is constantly evolving to keep pace with developments in the broad areas of wireless communications and networking.

This book is devoted to the study of control and stability in NCS. This monograph, an offshoot of the workshop held at Lund University, Lund, Sweden from October 17-19, 2012, contains contributions from leading researchers in control theory. The entire monograph is logically divided into three parts with each part consisting of three chapters. The first part deals with the controllability of stochastic dynamical systems with bandwidth and power constraints on communication channels used in the feedback loop. The second part explores the role of information in the controllability of stochastic dynamical systems. Finally, the third part deals with the routing of information in NCS. It also considers the problem of fault detection in smart grids based on Markov random fields. The following paragraphs focus on chapters 1 through 3, which address the broad theme of NCS.

Chapter 1 adopts a tutorial style toward the topic of controllability of dynamical systems under constraints imposed on communication channels used in the feedback loop. It starts off by giving a quick overview of NCS by abstracting them using discrete-time linear state space model equations. This is followed by a detailed exposition on the celebrated data rate theorem, which essentially specifies a lower bound (that depends on the unstable system modes) on the rate of feedback channel that ensures the ability of the underlying system to be stabilized. Next, the authors discuss how error-correcting codes can be designed to ensure stability of the underlying system. The chapter culminates with a discussion on the general framework for analyzing the data rate theorem based on Markov jump linear systems.

Chapter 2 is focused on mean-square stabilization of discrete-time linear-time invariant (LTI) systems over different types of communication channels, namely point-to-point and relay. To drive home the key results and insights, the authors use system models that are not comprised of more than two sensor nodes, although references for general system models are provided at relevant places. The chapter ends with a discussion on how a distributed sensor network can be used for controlling the underlying systems over point-to-point communication channels between the various sensors and the controller.

Chapter 3 combines the energy efficiency of a sensor node with the stability of NCS. Specifically, the authors formulate the problem of optimal radio mode selection in a sensor node at every decision epoch so as to minimize the cost function that accounts for both the performance of the feedback loop of NCS and energy consumption of the sensor. The authors prove the existence of an optimal stationary policy for the proposed problem and then look at its computation by the value-iteration method. The various other chapters in the book focus on topics that are as diverse as decentralized stochastic control, routing in networks, and the problem of fault detection in smart grids using random graphs.

In conclusion, the monograph delves specifically into the control aspects of NCS and feedback-based systems in general. Due to the mathematical sophistication required, it is ideally suitable for seasoned researchers in the area of control systems, although beginners could benefit by reading the introductory sections of various chapters. This book is a must-read for researchers who work at the intersection of communications, control, and information theory.