This book is concerned with the fault estimation problem for network systems. Firstly, to improve the existing adaptive fault estimation observer, a novel so-called intermediate estimator is proposed to identify the actuator or sensor faults in dynamic control systems with high accuracy and convergence speed. On this basis, by exploiting the properties of network systems such as multi-agent systems and large-scale interconnected systems, this book introduces the concept of distributed intermediate estimator; faults in different nodes can be estimated simultaneously; meanwhile, satisfactory consensus performances can be obtained via compensation based protocols. Finally, the characteristics of the new fault estimation methodology are verified and discussed by a series of experimental results on networked multi-axis motion control systems. This book can be used as a reference book for researcher and designer in the field of fault diagnosis and fault-tolerant control and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities.
Author(s): Jun-Wei Zhu, Xin Wang, Guang-Hong Yang
Publisher: Springer
Year: 2022
Language: English
Pages: 190
City: Singapore
Preface
Acknowledgements
Contents
Acronyms
1 Introduction
1.1 Background
1.2 Basic Concepts in Fault Diagnosis
1.3 FE Method and Research Status
1.4 Research Status for FTC
1.5 Book Outline
2 IE for Lipschitzian Nonlinear Systems
2.1 Introduction
2.2 Problem Statement and Preliminaries
2.3 Design of the IE
2.3.1 The IE Design for Nonlinear Systems with Single Faults
2.3.2 Extension of IE for Nonlinear Systems with Multiple Faults
2.4 Simulation Example
2.4.1 Example I
2.4.2 Example II
2.5 Conclusion
3 IE for Uncertain Systems
3.1 Introduction
3.2 Preliminaries and Problem Statement
3.3 The Design of the IE-Based FA Strategy
3.4 Example
3.4.1 Example 1
3.4.2 Example 2
3.5 Conclusion
4 IE for Time-Varying Delay Systems
4.1 Introduction
4.2 Problem Statement and Preliminaries
4.3 IE-Based FTC Scheme
4.4 Simulation Example
4.5 Conclusion
5 Distributed IE for Complex Networks
5.1 Introduction
5.2 Preliminaries and Problem Statement
5.2.1 Basic Graph Theory
5.2.2 Problem Statement
5.3 The Design of the Distributed IEs
5.4 Simulation Example
5.4.1 Example I
5.4.2 Example II
5.5 Conclusion
6 Distributed IE for MASs with Undirected Graph
6.1 Introduction
6.2 Preliminaries and Problem Statement
6.2.1 Basic Graph Theory
6.2.2 Problem Statement
6.3 The Design of the Distributed IE Based Fault Tolerant Tracking Protocol
6.4 Simulation Example
6.5 Conclusion
7 Distributed IE for MASs with Directed Graph
7.1 Introduction
7.2 Preliminaries and Problem Statement
7.3 The Design of the IE-based Tracking Protocol
7.4 Simulation Example
7.5 Conclusion
8 Intelligent IE for MASs
8.1 Introduction
8.2 Preliminaries and Problem Statement
8.2.1 Graph Theory
8.2.2 Problem Statement
8.3 Main Results
8.3.1 A Novel Observer-based CFTTC Protocol with Adaptive Switching Mechanism
8.3.2 Stability Analysis
8.3.3 CFTTC with Online Reinforcement Learning Estimation Strategy
8.4 Application to Networked Multi-Axis Motion Control System
8.4.1 Platform of Servo Motors
8.4.2 Experimental Results
8.5 Conclusion
9 IE for LPV Systems
9.1 Introduction
9.2 Problem Description
9.2.1 Kinematic Model of Mobile Robot
9.2.2 Problem Formulation
9.3 Main Result
9.3.1 Design of the Iterative IE with TDGRM
9.3.2 Stability Analysis of Estimation Error System
9.4 Application to Mobile Robot
9.5 Conclusion
10 Projected IE for CPSs
10.1 Introduction
10.2 Preliminaries and Problem Statement
10.2.1 System Description
10.2.2 Problem Statement
10.3 Main Results
10.3.1 Observability Analysis
10.3.2 The Design of Basic Steps for PIE
10.3.3 Algorithm
10.3.4 Stability Analysis
10.4 Application to Networked Motion Control System
10.5 Conclusion
11 Conclusions and Future Research Directions
11.1 Conclusion
Appendix References
Index
