Название: Recursive Filtering for 2-D Shift-Varying Systems with Communication ConstraintsАвтор: Jinling Liang, Zidong Wang, Fan Wang
Издательство: CRC Press
Год: 2022
Страниц: 245
Язык: английский
Формат: pdf (true)
Размер: 15.5 MB
This 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.
Two-dimensional (2-D) systems have been receiving a steadily growing research interest for their promising application insights in various engineering fields including image processing, electricity transmission, chemical processes, and multi-variable networks. In contrast with the traditional 1-D systems whose state evolves along a single direction, the information in 2-D systems propagates along two independent directions, thereby capable of modeling many real-world systems. It is crucial to reconstruct/estimate the system states of interest. Although considerable attention has been paid to 2-D filtering issues, the counterparts for 2-D shift-varying systems have been greatly neglected, where the conventional filtering techniques for shift-invariant systems are inapplicable anymore. On the other hand, communication constraints are inevitable for systems over communication networks, which may result in a variety of undesirable phenomena including measurement degradations, sensor delays, signal quantization, and so forth. All these phenomena play an important role in estimating the true states and have a great influence on the filtering performance. The traditional filtering methods have limitations in handling the filtering problems for 2-D shift-varying systems with communication constraints, and new recursive filtering strategies are of urgency to be developed, which motivates the current research.
The primary objective of this book is to present the up-to-date research developments and novel methodologies regarding recursive filtering for 2-D shift-varying systems with varieties of communication constraints. A systematic investigation on recursive filter/estimator design and performance analysis has been developed in the 2-D framework. A combination of the intensive stochastic analysis, recursive Riccati-like equations, variance-constrained approach, and matrix decomposition technique is utilized to subtly design the filter gains and expound effects of communication constraints on the filtering performance. Moreover, this book provides valuable reference materials for researchers who wish to explore the area of 2-D filtering issues.
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.
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