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Birkhäuser - Birkhäuser Engineering | Estimation and Control over Communication Networks

Estimation and Control over Communication Networks

Matveev, Alexey S., Savkin, Andrey V.

2009

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  • First book that attempts to present a systematic theory of estimation and control over communication networks, an increasingly active area of research
  • Addresses a class of problems that is quickly increasing due to the growing use of communication networks and large numbers of sensors, which may become the most important area of control theory in the near future
  • Many real-world applications: limited capacity communication channels, noisy discrete channels, systems with disturbances, irregular transmission times, and switched sensors
  • 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.

Content Level » Research

Keywords » Information - Optimal control - Shannon - Shannon information theory - Signal - Switch - communication - communication networks - control - entropy - entropy theory of dynamical systems - estimation - information theory - limited capacity communication channels - noisy discrete channels

Related subjects » Birkhäuser Computer Science - Birkhäuser Engineering - Birkhäuser Mathematics

Table of contents 

Preface Introduction Topological Entropy, Observability, Robustness, Stabilizability, and Optimal Control Stabilization of Linear Multiple Sensor Systems via Limited Capacity Communication Channels Detectability and Output Feedback Stabilizability of Nonlinear Systems via Limited Capacity Communication Channels Robust Set-Valued State Estimation via Limited Capacity Communication Channels An Analog of Shannon Information Theory: State Estimation and Stabilization of Linear Noiseless Plants via Noisy Discrete Channels An Analog of Shannon Information Theory: State Estimation and Stabilization of Linear Noisy Plants via Noisy Discrete Channels An Analog of Shannon Information Theory: Stable in Probability Control and State Estimation of Linear Noisy Plants via Noisy Discrete Channels Decentralized Stabilization of Linear Systems via Limited Capacity Communication Networks H-infinity State Estimation via Communication Channels Kalman State Estimation and Optimal Control Based on Asynchronously and Irregularly Delayed Measurements Optimal Computer Control via Asynchronous Communication Channels Linear-Quadratic Gaussian Optimal Control via Limited Capacity Communication Channels Kalman State Estimation in Networked Systems with Asynchronous Communication Channels and Switched Sensors Robust Kalman State Estimation with Switched Sensors Appendix A: Proof of Proposition 7.6.13 Appendix B: Some Properties of Square Ensembles of Matrices Appendix C: Discrete Kalman Filter and Linear-Quadratic Gaussian Optimal Control Problem Appendix D: Some Properties of the Joint Entropy of a Random Vector and Discrete Quantity References Index

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