Event-Based State Estimation A Stochastic Perspective / [electronic resource] :
by Dawei Shi, Ling Shi, Tongwen Chen.
- 1st ed. 2016.
- XIII, 208 p. 37 illus., 32 illus. in color. online resource.
- Studies in Systems, Decision and Control, 41 2198-4190 ; .
- Studies in Systems, Decision and Control, 41 .
Introduction -- Linear Gaussian Systems and Event-Based State Estimation -- Event-Triggered Sampling -- Approximate Optimal Filtering Approaches -- Constrained Optimization Approach -- Set-Valued Filtering Approach -- Probabilistic Approach -- Communications Rate Analysis -- Open Problems -- Appendices: Brief Review of Probability Theory; Linear Estimation Theory.
This book explores event-based estimation problems. It shows how several stochastic approaches are developed to maintain estimation performance when sensors perform their updates at slower rates only when needed. The self-contained presentation makes this book suitable for readers with no more than a basic knowledge of probability analysis, matrix algebra and linear systems. The introduction and literature review provide information, while the main content deals with estimation problems from four distinct angles in a stochastic setting, using numerous illustrative examples and comparisons. The text elucidates both theoretical developments and their applications, and is rounded out by a review of open problems. This book is a valuable resource for researchers and students who wish to expand their knowledge and work in the area of event-triggered systems. At the same time, engineers and practitioners in industrial process control will benefit from the event-triggering technique that reduces communication costs and improves energy efficiency in wireless automation applications. .
9783319266060
10.1007/978-3-319-26606-0 doi
Control engineering. Probabilities. Electric power production. System theory. Control theory. Control and Systems Theory. Probability Theory. Electrical Power Engineering. Systems Theory, Control .