Recursive Filtering for 2-D Shift-Varying Systems with Communication Constraints
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Jinling Liang, Zidong Wang, Fan WangThis 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.
It presents research developments and novel methodologies for recursive filtering for 2-D shift-varying systems with communication constraints. It investigates recursive filter/estimator design and performance analysis explaining dynamics of the system, subtle design of filter gains, effects of the communication constraints on performance.
1. 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.