Estimation and Control over Communication Networks [Hardcover]

This book presents a systematic theory of estimation and control over communication networks. It develops a theory that utilizes communications, control, information and dynamical systems theory motivated and applied to advanced networking scenarios. The book establishes theoretically rich and practically important connections among modern control theory, Shannon information theory, and entropy theory of dynamical systems originated in the work of Kolmogorov.

This self-contained monograph covers the latest achievements in the area. It contains many real-world applications and the presentation is accessible.

This book presents a systematic theory of estimation and control over communication networks. The book addresses a class of problems that is quickly increasing due to the growing use of communication networks and large numbers of sensors.

Rapid advances in communication technology have created the possibility of large-scale control systems with distribution of control tasks among several processors via communication channels. Such control systems may be distributed over large distances and may use large numbers of actuators and sensors. The possibility of such networked control systems has motivated the development of a new chapter in control theory in which control and communication issues are integrated, and all the limitations of communication channels are considered.

Although there is an emerging literature on this topic, this is the first book that attempts to present a systematic theory of estimation and control over communication networks. Using several selected problems of estimation and control over communication networks, the authors present and prove a number of results concerning optimality, stability, and robustness having practical significance for networked control system design. In particular, various problems of Kalman filtering, stabilization, and optimal control l“+