Distributed Fault-Tolerant Consensus Control of Leader-Following Systems: Based on Adaptive Control Approach (Intelligent Control and Learning Systems, 11)

✍ Scribed by Qikun Shen

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 197
• Category: Library

✦ Synopsis

This book provides recent theoretical results and applications of the consensus control for nonlinear leader-following systems. Combining adaptive control technique, fuzzy logic systems, neural networks with the other control techniques or approaches, this book investigates the consensus control problem of leader-following systems and proposes the corresponding control scheme. This book intends to provide the readers a good understanding on consensus control based on adaptive control technology. This book can serve as a reference for the main research issues and results on nonlinear multi-agent systems including leader-following systems for researchers devoting to various areas of control theory, as well as a material for graduate and undergraduate students interested in nonlinear multi-agent systems including leader-following systems and their applications. Some prerequisites for reading this book include nonlinear system theory, matrix theory, mathematics, basic graph theory, and soon.

✦ Table of Contents

Preface
Contents
Acronyms
1 Introduction
1.1 Fault Types in MASs: Local and Global Faults
1.2 Fault-Tolerant Control Against Local Faults
1.3 Fault-Tolerant Control Against Global Faults
1.4 Organization of the Book
References
2 Distributed Cooperative Neural Fault-Tolerant Sliding Mode Control Against Actuator Faults
2.1 Introduction
2.2 Problem Formation
2.2.1 Basic Graph Theory
2.2.2 Problem Formulation
2.2.3 Neural Networks
2.3 Main Results
2.3.1 Cooperative Control Without Faults and Fault Detection
2.3.2 Distributed FTC Against Actuator Faults
2.4 Simulation
2.5 Conclusion
References
3 Distributed Cooperative Fuzzy Fault-Tolerant Backstepping Control Against Dead-Zone and Saturation
3.1 Introduction
3.2 Preliminaries and Problem Formulation
3.2.1 Preliminaries
3.2.2 Problem Formulation
3.2.3 Descriptions of Saturation and Dead-Zone
3.2.4 Fuzzy Logic Systems
3.3 Main Results
3.4 Simulation
3.4.1 Descriptions of AUVs
3.4.2 Simulation Results
3.5 Conclusion
References
4 Distributed Neural Fault-Tolerant Supervisory Control Against Backlash-Like Hysteresis
4.1 Introduction
4.2 Problem Formulation and Preliminaries
4.2.1 Basic Graph Theory
4.2.2 Problem Formulation
4.2.3 Backlash-Like Hysteresis
4.2.4 Mathematical Description of Neural Networks
4.3 Main Results
4.4 Example
4.5 Conclusion
References
5 Distributed Fuzzy Fault-Tolerant Output Consensus Control Against Unknown Nonlinear Dead-Zone
5.1 Introduction
5.2 Preliminaries and Problem Formulation
5.2.1 Basic Graph Theory and Preliminaries
5.2.2 Problem Formation
5.2.3 Description of Dead-Zone
5.2.4 Fuzzy Logic Systems
5.3 Main Results
5.4 Simulation
5.5 Conclusion
References
6 Adaptive Fault-Tolerant Consensus Control Against Communication Faults
6.1 Introduction
6.2 Problem Formulation and Preliminaries
6.2.1 Notations and Basic Graph Theory
6.2.2 Problem Formulation
6.2.3 Models of Transmission Faults
6.3 Main Results
6.3.1 Fault-Tolerant Consensus Control Against Transmission Gain Faults
6.3.2 Fault-Tolerant Consensus Control Against Transmission Bias Faults
6.4 Simulation Results
6.5 Conclusion
References
7 Cooperative Fault-Tolerant Neural Control Against Signal Communication Faults
7.1 Introduction
7.2 Preliminaries and Problem Formation
7.2.1 Basic Graph Theory
7.2.2 Problem Formulation
7.2.3 Neural Networks
7.3 Main Results
7.4 Simulation Results
7.5 Conclusions
References
8 Filter-Based Distributed Fault-Tolerant Neural Control Against Sensor Faults
8.1 Introduction
8.2 Preliminaries
8.2.1 Graph Theory
8.2.2 Problem Formulation
8.2.3 Neural Networks
8.3 Main Results
8.3.1 Filter Design
8.3.2 Fault-Tolerant Controller Design
8.3.3 Stability Analysis
8.4 Simulation
8.5 Conclusion
References
9 Conclusion and Future Research Directions
9.1 Conclusions
9.2 Future Research Directions