Muutke küpsiste eelistusi

Networked Nonlinear Stochastic Time-Varying Systems: Analysis and Synthesis [Kõva köide]

(Brunel Uni, UK), (Northeast Petroleum University, China.), (Northeast Petroleum University, China.)
  • Formaat: Hardback, 256 pages, kõrgus x laius: 234x156 mm, kaal: 670 g, 19 Tables, black and white; 27 Line drawings, black and white; 27 Halftones, black and white; 54 Illustrations, black and white
  • Ilmumisaeg: 10-Sep-2021
  • Kirjastus: CRC Press
  • ISBN-10: 1032038780
  • ISBN-13: 9781032038780
Teised raamatud teemal:
Networked Nonlinear Stochastic Time-Varying Systems: Analysis and SynthesisSuurem pilt
  • Formaat: Hardback, 256 pages, kõrgus x laius: 234x156 mm, kaal: 670 g, 19 Tables, black and white; 27 Line drawings, black and white; 27 Halftones, black and white; 54 Illustrations, black and white
  • Ilmumisaeg: 10-Sep-2021
  • Kirjastus: CRC Press
  • ISBN-10: 1032038780
  • ISBN-13: 9781032038780
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781032038780.html
Märksõnad:

This book copes with the filter design, fault estimation and reliable control problems for different classes of nonlinear stochastic time-varying systems with network-enhanced complexities (e.g. state-multiplicative noises, stochastic nonlinearities, stochastic inner couplings, channel fadings, measurement quantizations etc).



Networked Non-linear Stochastic Time-Varying Systems: Analysis and Synthesis copes with the filter design, fault estimation and reliable control problems for different classes of nonlinear stochastic time-varying systems with network-enhanced complexities. Divided into three parts, the book discusses the finite-horizon filtering, fault estimation and reliable control, and randomly occurring nonlinearities/uncertainties followed by designing of distributed state and fault estimators, and distributed filters. The third part includes problems of variance-constrained H8 state estimation, partial-nodes-based state estimation and recursive filtering for nonlinear time-varying complex networks with randomly varying topologies, and random coupling strengths.

  • Offers a comprehensive treatment of the topics related to Networked Nonlinear Stochastic Time-Varying Systems with rigorous math foundation and derivation

  • Unifies existing and emerging concepts concerning control/filtering/estimation and distributed filtering

  • Provides a series of latest results by drawing on the conventional theories of systems science, control engineering and signal processing Deal with practical engineering problems such as event triggered H8 filtering, non-fragile distributed estimation, recursive filtering, set-membership filtering

  • Demonstrates illustrative examples in each chapter to verify the correctness of the proposed results

This book is aimed at engineers, mathematicians, scientists, and upper-level students in the fields of control engineering, signal processing, networked control systems, robotics, data analysis, and automation.

Preface xi
List of Figures
xiii
List of Tables
xv
Acknowledgments xvii
Symbols xix
List of Acronyms
xxi
1 Introduction
1(24)
1.1 Background
3(16)
1.1.1 Nonlinear Stochastic Time-Varying Systems
3(1)
1.1.2 Network-Enhanced Complexities
4(8)
1.1.3 Filter Design, Fault Estimation and Reliable Control
12(7)
1.2 Outline
19(6)
2 Event-Triggered Multi-objective Filtering and Control
25(38)
2.1 Event-Triggered H∞ Filtering with Fading Channels
25(10)
2.1.1 Problem Formulation
26(3)
2.1.2 Design of Filter Gain
29(6)
2.2 Event-Triggered Variance-Constrained Control
35(15)
2.2.1 Problem Formulation
36(4)
2.2.2 Finite-Horizon Controller Design
40(10)
2.3 Illustrative Examples
50(11)
2.3.1 Example 1
50(2)
2.3.2 Example 2
52(9)
2.4 Summary
61(2)
3 Finite-Horizon Reliable Control Subject to Output Quantization
63(16)
3.1 Problem Formulation
63(4)
3.2 Reliable Controller Design
67(8)
3.3 An Illustrative Example
75(2)
3.4 Summary
77(2)
4 Finite-Horizon Estimation of Randomly Occurring Faults
79(30)
4.1 On Hoc Estimation of ROFs with Fading Channels
79(10)
4.1.1 Problem Formulation
80(3)
4.1.2 Main Results
83(6)
4.2 Recursive Estimation of ROFs: the Finite-Horizon Case
89(10)
4.2.1 Problem Formulation
89(3)
4.2.2 Main Results
92(7)
4.3 Illustrative Examples
99(5)
4.3.1 Example 1
99(4)
4.3.2 Example 2
103(1)
4.4 Summary
104(5)
5 Set-Membership Filtering under Weighted Try-Once-Discard Protocol
109(10)
5.1 Problem Formulation
109(3)
5.2 Main Results
112(3)
5.2.1 Filter Design Subject to the P(k)-Dependent Constraint
112(2)
5.2.2 Minimizing the Ellipsoids with Inequality Constraints
114(1)
5.3 An Illustrative Example
115(1)
5.4 Summary
116(3)
6 Distributed Estimation over Sensor Network
119(40)
6.1 Finite-Horizon Distributed State Estimation with RSTs and RCs
120(11)
6.1.1 Problem Formulation
120(4)
6.1.2 Main Results
124(7)
6.2 Non-Fragile Distributed Fault Estimation: the Finite-Horizon Case
131(8)
6.2.1 Problem Formulation
131(3)
6.2.2 Main Results
134(5)
6.3 Distributed Filtering with RSTs under the RR Protocol
139(8)
6.3.1 Problem Formulation
139(4)
6.3.2 Main Results
143(4)
6.4 Illustrative Examples
147(8)
6.4.1 Example 1
147(1)
6.4.2 Example 2
148(5)
6.4.3 Example 3
153(2)
6.5 Summary
155(4)
7 State Estimation for Complex Networks
159(44)
7.1 State Estimation with Randomly Varying Topologies
160(16)
7.1.1 Problem Formulation
160(5)
7.1.2 Analysis of H∞ and Covariance Performances
165(5)
7.1.3 Design of Finite-Horizon State Estimators
170(6)
7.2 Partial-Nodes-Based State Estimation under Random Access Protocol
176(14)
7.2.1 Problem Formulation
176(6)
7.2.2 Main Results
182(8)
7.3 Illustrative Examples
190(9)
7.3.1 Example 1
190(1)
7.3.2 Example 2
191(8)
7.4 Summary
199(4)
8 Event-Triggered Recursive Filtering for Complex Networks with Random Coupling Strengths
203(28)
8.1 Problem Formulation
203(3)
8.2 Main Results
206(16)
8.3 Illustrative Examples
222(8)
8.3.1 Example 1
222(1)
8.3.2 Example 2
223(7)
8.4 Summary
230(1)
9 Conclusions and Future Work
231(4)
9.1 Conclusions
231(3)
9.2 Future Work
234(1)
Bibliography 235(20)
Index 255
Hongli Dong, Zidong Wang, Nan Hou