Robust Observer-Based Fault Diagnosis for Nonlinear Systems Using MATLAB®

✍ Scribed by Jian Zhang, Akshya Kumar Swain, Sing Kiong Nguang

• Publisher: Springer
• Year: 2016
• Tongue: English
• Leaves: 231
• Series: Advances in Industrial Control
• Edition: 1st ed. 2016
• Category: Library

✦ Synopsis

This book introduces several observer-based methods, including:

• the sliding-mode observer

• the adaptive observer

• the unknown-input observer and

• the descriptor observer method

for the problem of fault detection, isolation and estimation, allowing readers to compare and contrast the different approaches. The authors present basic material on Lyapunov stability theory, H¥ control theory, sliding-mode control theory and linear matrix inequality problems in a self-contained and step-by-step manner. Detailed and rigorous mathematical proofs are provided for all the results developed in the text so that readers can quickly gain a good understanding of the material. MATLAB® and Simulink® codes for all the examples, which can be downloaded from http://extras.springer.com, enable students to follow the methods and illustrative examples easily. The systems used in the examples make the book highly relevant to real-world problems in industrial control engineering and include a seventh-order aircraft model, a single-link flexible joint robot arm and a satellite controller. To help readers quickly find the information they need and to improve readability, the individual chapters are written so as to be semi-independent of each other.

Robust Oberserver-Based Fault Diagnosis for Nonlinear Systems Using MATLAB® is of interest to process, aerospace, robotics and control engineers, engineering students and researchers with a control engineering background.

✦ Table of Contents

Series Editors’ Foreword
Preface
Contents
Abbreviations
1 Introduction
1.1 Fault Diagnosis Methodologies
1.2 Robust Observer-Based Fault Diagnosis: An Overview
1.3 Outline of the Book
References
2 Detection and Isolation of Actuator Faults
2.1 Introduction
2.2 Problem Formulation
2.3 Actuator FD Scheme
2.4 Actuator FI Scheme
2.5 Simulation Results
2.6 Conclusions
References
3 Detection and Isolation of Sensor Faults
3.1 Introduction
3.2 Problem Formulation
3.3 Sensor FD Scheme
3.4 Sensor FI Scheme
3.5 Simulation Results
3.6 Conclusions
References
4 Robust Estimation of Actuator Faults
4.1 Introduction
4.2 Problem Formulation
4.3 Actuator FE Scheme
4.3.1 Observer Design
4.3.2 Estimation of Actuator Faults
4.4 A Generalization to Sensor FE
4.4.1 Observer Design
4.4.2 Estimation of Sensor Faults
4.5 Simulation Results
4.5.1 Actuator Fault Estimation
4.5.2 Sensor Fault Estimation
4.6 Conclusions
References
5 Robust Estimation of Sensor Faults
5.1 Introduction
5.2 Problem Formulation
5.3 SMO-Based Sensor FE
5.4 AO-Based Sensor FE
5.5 Simulation Results
5.6 Conclusions
References
6 Simultaneous Estimation of Actuator and Sensor Faults Using SMO and AO
6.1 Introduction
6.2 Problem Formulation
6.3 SMOs-Based FE Scheme
6.3.1 Design of Observers
6.3.2 Estimation of Faults
6.4 SMO- and AO-Based FE Scheme
6.4.1 Design of Observers
6.4.2 Estimation of Faults
6.5 Simulation Results
6.6 Conclusions
References
7 Simultaneous Estimation of Actuator and Sensor Faults Using SMO and UIO
7.1 Introduction
7.2 Problem Formulation
7.3 Design of Observers
7.4 Estimation of Faults
7.5 Simulation Results
7.6 Conclusions
References
8 Simultaneous Estimation of Actuator and Sensor Faults for Descriptor Systems
8.1 Introduction
8.2 Problem Formulation
8.3 Design of Observer
8.4 Simulation Results
8.4.1 Example of FE for Descriptor Systems
8.4.2 Example of FE for Normal Systems
8.5 Conclusion
References
9 Conclusions and Future Work
9.1 Conclusions
9.2 Future Work
References
Appendix ASolving Linear Matrix Inequality (LMI)Problems
Appendix BYALMIP Toolbox: A Short Tutorial
Index