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OverviewThis book presents up-to-date research developments and novel methodologies regarding recursive filtering for 2-D shift-varying systems with various communication constraints. It investigates recursive filter/estimator design and performance analysis by a combination of intensive stochastic analysis, recursive Riccati-like equations, variance-constrained approach, and mathematical induction. Each chapter considers dynamics of the system, subtle design of filter gains, and effects of the communication constraints on filtering performance. Effectiveness of the derived theories and applicability of the developed filtering strategies are illustrated via simulation examples and practical insight. Features:- Covers recent advances of recursive filtering for 2-D shift-varying systems subjected to communication constraints from the engineering perspective. Includes the recursive filter design, resilience operation and performance analysis for the considered 2-D shift-varying systems. Captures the essence of the design for 2-D recursive filters. Develops a series of latest results about the robust Kalman filtering and protocol-based filtering. Analyzes recursive filter design and filtering performance for the considered systems. This book aims at graduate students and researchers in mechanical engineering, industrial engineering, communications networks, applied mathematics, robotics and control systems. Full Product DetailsAuthor: Jinling Liang (School of Mathematics, Southeast University.) , Zidong Wang (Brunel Un., London, UK) , Fan Wang (Southeast University, Nanjing, China.)Publisher: Taylor & Francis Ltd Imprint: CRC Press Weight: 0.450kg ISBN: 9781032038223ISBN 10: 1032038225 Pages: 222 Publication Date: 09 October 2024 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Forthcoming Availability: Not yet available  This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release. Table of Contents1. Introduction. 2. Minimum-Variance Recursive Filtering for Two-Dimensional Systems with Degraded Measurements: Boundedness and Monotonicity. 3. Robust Kalman Filtering for Two-Dimensional Systems with Multiplicative Noises and Measurement Degradations. 4. Robust Finite-Horizon Filtering for Two-Dimensional Systems with Randomly Varying Sensor Delays. 5. Recursive Filtering for Two-Dimensional Systems with Missing Measurements subject to Uncertain Probabilities. 6. Resilient State Estimation for Two-Dimensional Shift-Varying Systems with Redundant Channels. 7. Recursive Distributed Filtering for Two-Dimensional Shift-Varying Systems Over Sensor Networks Under Random Access Protocols. 8. Resilient Filtering for Linear Shift-Varying Repetitive Processes under Uniform Quantization and Round-Robin Protocols. 9. Event-Triggered Recursive Filtering for Shift-Varying Linear Repetitive Processes. 10. Conclusions and Future Topics.ReviewsAuthor InformationJinling Liang, Zidong Wang, Fan Wang Tab Content 6Author Website:Countries AvailableAll regions |
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