Event-Based State Estimation A Stochastic Perspective - Shi, Dawei; Shi, Ling.; Chen, Tongwen; SpringerLink (Online service) (Cham : Springer International Publishing : Imprint: Springer, 2016)
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. .
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.
Keywords: Engineering; System theory; Probabilities; Control engineering; Power electronics; Engineering; Control; Probability Theory and Stochastic Processes; Power Electronics, Electrical Machines and Networks; Systems Theory, Control; Electronic books