Beschreibung:
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.
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. The results establish fundamental links among mathematical control theory, Shannon information theory, and entropy theory of dynamical systems.
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.- H1 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.
