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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
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