This book investigates in detail model-based fault diagnosis methods, including observer-based residual generation, residual evaluation based on threshold computation, observer-based fault isolation strategies, observer-based fault estimation, Kalman filter-based fault diagnosis methods, and parity space approach. Studies on model-based fault diagnosis have attracted engineers and scientists from various disciplines, such as electrical, aerospace, mechanical, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of state-space approach. The methods introduced in the book are systemic and easy to follow. The book is intended for undergraduate and graduate students who are interested in fault diagnosis and state estimation, researchers investigating fault diagnosis and fault-tolerant control, and control system design engineers working on safety-critical systems.
Author(s): Zhenhua Wang, Yi Shen
Series: Studies in Systems, Decision and Control, 221
Publisher: Springer
Year: 2022
Language: English
Pages: 206
City: Singapore
Preface
Contents
Acronyms
Notation
1 Introduction
1.1 Basic Concepts in Fault Diagnosis
1.2 Model-Based Fault Diagnosis Methods
1.2.1 Observer-Based Methods
1.2.2 Parity Space Approaches
1.2.3 Parameter Estimation Methods
1.3 Outline of the Book
References
2 Modelling for Fault Diagnosis
2.1 Modelling of Nominal Systems
2.2 Modelling of Faults
2.3 Description of Uncertainties
2.4 Conclusion
References
3 Observer-Based Residual Generation
3.1 Residual Generation Based on Analytical Redundancy
3.2 Observer-Based Residual Generation for Continuous-Time Systems
3.3 Observer-Based Residual Generation for Discrete-Time Systems
3.4 Conclusion
References
4 Robust Residual Generation Based on Unknown Input Observer
4.1 UIO-Based Residual Generation for Continuous-Time Systems
4.2 UIO-Based Residual Generation for Discrete-Time Systems
4.3 Conclusion
References
5 Optimal Robust Residual Generation
5.1 Optimal Robust Residual Generation for Continuous-Time Systems
5.2 Optimal Robust Residual Generation for Discrete-Time Systems
5.3 Conclusion
References
6 Residual Evaluation Based on Threshold Computation
6.1 Residual Evaluation Based on Peak-to-Peak Analysis
6.1.1 Residual Evaluation for Continuous-Time Systems
6.1.2 Residual Evaluation for Discrete-Time Systems
6.2 Residual Evaluation Based on Interval Analysis
6.2.1 Residual Evaluation for Continuous-Time Systems
6.2.2 Residual Evaluation for Discrete-Time Systems
6.3 Conclusion
References
7 Fault Isolation Based on Structured Residual Generation
7.1 Sensor Fault Isolation Based on Dedicated Observer Scheme
7.2 Sensor Fault Isolation Based on Simplified Observer Scheme
7.3 Sensor Fault Isolation Based on Generalized Observer Scheme
7.4 Actuator Fault Isolation Based on Structured Residual Generation
7.5 Conclusion
References
8 Fault Isolation Based on Directional Residual Generation
8.1 Observer-Based Directional Residual Generator
8.2 Directional Residual Generator Design for Systems with Fully Measurable States
8.3 Directional Residual Generator Design for General LTI Systems
8.4 FDI Based on Directional Residual Generation
8.5 Conclusion
References
9 Observer-Based Fault Estimation
9.1 Adaptive Observer-Based Fault Estimation
9.2 Fault Estimation Based on Augmented State Observer
9.3 Conclusion
References
10 Kalman Filter-Based Fault Diagnosis
10.1 Kalman Filter-Based Fault Detection
10.2 Fault Isolation Based on Dedicated Kalman Filters
10.3 Fault Estimation Based on Augmented State Kalman Filter
10.4 Conclusion
References
11 Parity Space Approaches
11.1 Residual Generation Using Parity Space Approach
11.1.1 Basic Parity Space Approach
11.1.2 Optimal Parity Space Approach
11.2 Residual Evaluation Methods in Parity Space Approach
11.2.1 Norm-Based Analysis Method
11.2.2 Interval-Based Analysis Method
11.2.3 Statistic Test Method
11.3 Fault Isolation Strategies Based on Parity Space Approach
11.3.1 Structured Residual Generation Based on Parity Space Approach
11.3.2 Directional Residual Generation Based on Parity Space Approach
11.4 Conclusion
References
