Recursive Filtering for 2-D Shift-Varying Systems with Communication Constraints

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.

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.

Jinling Liang, Zidong Wang, Fan Wang