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Recursive Filtering for 2-D Shift-Varying Systems with Communication Constraints [Kõva köide]

(School of Mathematics, Southeast University.), (Brunel Uni, UK), (Southeast University, Nanjing, China.)
  • Formaat: Hardback, 222 pages, kõrgus x laius: 234x156 mm, kaal: 610 g, 4 Tables, black and white; 61 Line drawings, black and white; 61 Illustrations, black and white
  • Ilmumisaeg: 06-Sep-2021
  • Kirjastus: CRC Press
  • ISBN-10: 1032038179
  • ISBN-13: 9781032038179
Teised raamatud teemal:
Recursive Filtering for 2-D Shift-Varying Systems with Communication ConstraintsSuurem pilt
  • Formaat: Hardback, 222 pages, kõrgus x laius: 234x156 mm, kaal: 610 g, 4 Tables, black and white; 61 Line drawings, black and white; 61 Illustrations, black and white
  • Ilmumisaeg: 06-Sep-2021
  • Kirjastus: CRC Press
  • ISBN-10: 1032038179
  • ISBN-13: 9781032038179
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781032038179.html
Märksõnad:

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.



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.

Preface xi
Acknowledgments xiii
Author Biographies xv
List of Figures
xvii
List of Tables
xix
Symbols xxi
1 Introduction
1(22)
1.1 2-D Systems
1(4)
1.1.1 Some Classical 2-D Models
2(1)
1.1.2 Relationships between the Models
2(1)
1.1.3 Linear Repetitive Processes
3(1)
1.1.4 2-D Models with Other Complicated Dynamics
4(1)
1.2 Communication Constraints
5(7)
1.2.1 Network-Induced Phenomena
6(3)
1.2.2 Communication Protocols
9(3)
1.3 Recent Progress on Filtering for 2-D Systems
12(7)
1.3.1 #oo Filtering
12(2)
1.3.2 Z2-Zoo Filtering
14(1)
1.3.3 h Filtering
14(1)
1.3.4 Dissipative Filtering
15(1)
1.3.5 Kalman Filtering
15(1)
1.3.6 Variance-Constrained Filtering
16(2)
1.3.7 Protocol-Based Filtering
18(1)
1.4 Outline
19(4)
2 Minimum-Variance Recursive Filtering for 2-D Systems with Degraded Measurements: Boundedness and Monotonicity
23(26)
2.1 Problem Formulation
24(3)
2.2 The Minimum-Variance Filter Design
27(4)
2.3 Performance Analysis
31(9)
2.3.1 Boundedness Analysis
31(4)
2.3.2 Monotonicity Analysis
35(2)
2.3.3 Filtering Algorithm
37(3)
2.4 Numerical Example
40(7)
2.5 Summary
47(2)
3 Robust Kalman Filtering for 2-D Systems with Multiplicative Noises and Measurement Degradations
49(24)
3.1 Problem Formulation and Preliminaries
50(3)
3.2 Upper Bound for the Generalized Error Variance
53(4)
3.3 Suboptimal Filter Design
57(7)
3.4 Numerical Example
64(7)
3.5 Summary
71(2)
4 Robust Finite-Horizon Filtering for 2-D Systems with Randomly Varying Sensor Delays
73(22)
4.1 Problem Formulation
74(3)
4.2 Preliminaries
77(4)
4.3 Finite-Horizon Robust Kalman Filter Design
81(7)
4.4 Numerical Example
88(6)
4.5 Summary
94(1)
5 Recursive Filtering for 2-D Systems with Missing Measurements Subject to Uncertain Probabilities
95(12)
5.1 Problem Formulation
96(2)
5.2 Recursive Filter Design
98(4)
5.3 Numerical Example
102(4)
5.4 Summary
106(1)
6 Resilient State Estimation for 2-D Shift-Varying Systems with Redundant Channels
107(20)
6.1 Problem Formulation and Preliminaries
108(4)
6.2 Resilient Filter Design
112(7)
6.3 Numerical Examples
119(6)
6.4 Summary
125(2)
7 Recursive Distributed Filtering for 2-D Shift-Varying Systems Over Sensor Networks Under Random Access Protocols
127(24)
7.1 Problem Formulation and Preliminaries
129(4)
7.1.1 The System Model
129(1)
7.1.2 Random Access Protocol
130(1)
7.1.3 Distributed Filter
131(2)
7.2 Main Results
133(9)
7.3 Numerical Example
142(8)
7.4 Summary
150(1)
8 Resilient Filtering for Linear Shift-Varying Repetitive Processes under Uniform Quantizations and Round-Robin Protocols
151(26)
8.1 Problem Formulation
153(6)
8.1.1 The System Model
153(1)
8.1.2 Network Description
154(3)
8.1.3 Resilient Filter
157(2)
8.2 Main Results
159(11)
8.2.1 The Upper Bounds and Filter Design
161(4)
8.2.2 Boundedness Analysis
165(5)
8.3 Numerical Example
170(5)
8.4 Summary
175(2)
9 Event-Triggered Recursive Filtering for Shift-Varying Linear Repetitive Processes
177(18)
9.1 Problem Formulation
179(3)
9.1.1 Linear Repetitive Process
179(1)
9.1.2 Event-Triggered Mechanism
180(2)
9.2 Main Results
182(7)
9.3 Numerical Example
189(5)
9.4 Summary
194(1)
10 Conclusions and Future Topics
195(2)
Bibliography 197(24)
Index 221
Jinling Liang, Zidong Wang, Fan Wang