Estimation and Control over Communication Networks

Although there is an emerging literature on the 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 over communication channels are considered and solved. The results establish fundamental links among mathematical control theory, Shannon information theory, and entropy theory of dynamical systems.

This essentially self-contained monograph offers accessible mathematical models and results for advanced postgraduate students, researchers, and practitioners working in the areas of control engineering, communications, information theory, signal processing, and applied mathematics.

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 over communication channels are considered and solved. The results establish fundamental links among mathematical control theory, Shannon information theory, and entropy theory of dynamical systems.

Key features and topics of the work:

* Offers accessible but precise development of important mathematical models and results

* Covers estimation and stabilization of both linear and nonlinear systems

* Addresses limited capacity communication channels, noisy discrete channels, systems with disturbances, irregular transmission times, and switched sensors

* Presents state-of-the-art developments and cutting-edge results in the field

This essentially self-contained monograph offers accessible mathematical models and results for advanced postgraduate students, researchers, and practitioners working in the areas of control engineering, communications, information theory, signal processing, and applied mathematics who have an interest in the emerging field of networked control systems.