Recursive Filtering for 2 D Shift Varying Systems with Communication Constraints 1st Edition by Jinling Liang, Zidong Wang, Fan Wang 1032038225 9781032038223

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ISBN 10: 1032038225

ISBN 13: 9781032038223

Author: Jinling Liang, Zidong Wang, Fan Wang

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.

Recursive Filtering for 2 D Shift Varying Systems with Communication Constraints 1st Table of contents:

1 Introduction

1.1 2-D Systems

1.1.1 Some Classical 2-D Models

1.1.2 Relationships between the Models

1.1.3 Linear Repetitive Processes

1.1.4 2-D Models with Other Complicated Dynamics

1.2 Communication Constraints

1.2.1 Network-Induced Phenomena

1.2.2 Communication Protocols

1.3 Recent Progress on Filtering for 2-D Systems

1.3.1 H∞ Filtering

1.3.2 l2−l∞ Filtering

1.3.3 l1 Filtering

1.3.4 Dissipative Filtering

1.3.5 Kalman Filtering

1.3.6 Variance-Constrained Filtering

1.3.7 Protocol-Based Filtering

1.4 Outline

2 Minimum-Variance Recursive Filtering for 2-D Systems with Degraded Measurements: Boundedness and Monotonicity

2.1 Problem Formulation

2.2 The Minimum-Variance Filter Design

2.3 Performance Analysis

2.3.1 Boundedness Analysis

2.3.2 Monotonicity Analysis

2.3.3 Filtering Algorithm

2.4 Numerical Example

2.5 Summary

3 Robust Kalman Filtering for 2-D Systems with Multiplicative Noises and Measurement Degradations’

3.1 Problem Formulation and Preliminaries

3.2 Upper Bound for the Generalized Error Variance

3.3 Suboptimal Filter Design

3.4 Numerical Example

3.5 Summary

4 Robust Finite-Horizon Filtering for 2-D Systems with Randomly Varying Sensor Delays

4.1 Problem Formulation

4.2 Preliminaries

4.3 Finite-Horizon Robust Kalman Filter Design

4.4 Numerical Example

4.5 Summary

5 Recursive Filtering for 2-D Systems with Missing Measurements Subject to Uncertain Probabilities

5.1 Problem Formulation

5.2 Recursive Filter Design

5.3 Numerical Example

5.4 Summary

6 Resilient State Estimation for 2-D Shift-Varying Systems with Redundant Channels

6.1 Problem Formulation and Preliminaries

6.2 Resilient Filter Design

6.3 Numerical Examples

6.4 Summary

7 Recursive Distributed Filtering for 2-D Shift-Varying Systems Over Sensor Networks Under Random Access Protocols

7.1 Problem Formulation and Preliminaries

7.1.1 The System Model

7.1.2 Random Access Protocol

7.1.3 Distributed Filter

7.2 Main Results

7.3 Numerical Example

7.4 Summary

8 Resilient Filtering for Linear Shift-Varying Repetitive Processes under Uniform Quantizations and Round-Robin Protocols

8.1 Problem Formulation

8.1.1 The System Model

8.1.2 Network Description

8.1.3 Resilient Filter

8.2 Main Results

8.2.1 The Upper Bounds and Filter Design

8.2.2 Boundedness Analysis

8.3 Numerical Example

8.4 Summary

9 Event-Triggered Recursive Filtering for Shift-Varying Linear Repetitive Processes

9.1 Problem Formulation

9.1.1 Linear Repetitive Process

9.1.2 Event-Triggered Mechanism

9.2 Main Results

9.3 Numerical Example

9.4 Summary

10 Conclusions and Future Topics

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Tags: Jinling Liang, Zidong Wang, Fan Wang, Recursive, Filtering