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Book Description

Linear Systems: Non-Fragile Control and Filtering presents the latest research results and a systematic approach to designing non-fragile controllers and filters for linear systems. The authors combine the algebraic Riccati technique, the linear matrix inequality (LMI) technique, and the sensitivity analysis method to establish a set of new non-fragile (insensitive) control methods. This proposed method can optimize the closed-loop system performance and make the designed controllers or filters tolerant of coefficient variations in controller or filter gain matrices.

A Systematic Approach to Designing Non-Fragile Controllers and Filters for Linear Systems

The text begins with developments and main research methods in non-fragile control. It then systematically presents novel methods for non-fragile control and filtering of linear systems with respect to additive/multiplicative controller/filter gain uncertainties. The book introduces the algebraic Riccati equation technique to solve additive/multiplicative norm-bounded controller/filter gain uncertainty, and proposes a structured vertex separator to deal with the numerical problem resulting from interval-bounded coefficient variations. It also explains how to design insensitive controllers and filters in the framework of coefficient sensitivity theory. Throughout, the book includes numerical examples to demonstrate the effectiveness of the proposed design methods.

More Effective Design Methods for Non-Fragile Controllers and Filters

The design and analysis tools described will help readers to better understand and analyze parameter uncertainties and to design more effective non-fragile controllers and filters. Providing a coherent approach, this book is a valuable reference for researchers, graduate students, and anyone who wants to explore the area of non-fragile control and filtering.

1. Cover
2. Half Title
3. Title Page
6. Preface
7. Symbol Description
8. 1 Introduction
9. 2 Preliminaries
10. 3 Non-Fragile State Feedback Control with Norm-Bounded Gain Uncertainty
1. 3.1 Introduction
2. 3.2 Problem Statement
3. 3.3 Non-Fragile Guaranteed Cost Controller Design
4. 3.4 Example
5. 3.5 Conclusion
11. 4 Non-Fragile Dynamic Output Feedback Control with Norm-Bounded Gain Uncertainty
1. 4.1 Introduction
2. 4.2 Problem Statement
3. 4.3 Non-Fragile H∞ Dynamic Output Feedback Controller Design
4. 4.4 Example
5. 4.5 Conclusion
12. 5 Robust Non-Fragile Kalman Filtering with Norm-Bounded Gain Uncertainty
1. 5.1 Introduction
2. 5.2 Problem Statement
3. 5.3 Robust Non-Fragile Filter Design
4. 5.4 Example
5. 5.5 Conclusion
13. 6 Non-Fragile Output Feedback Control with Interval-Bounded Coefficient Variations
1. 6.1 Introduction
2. 6.2 Non-Fragile H∞ Controller Design for Discrete-Time Systems
3. 6.3 Non-Fragile H∞ Controller Design for Continuous-Time Systems
4. 6.4 Non-Fragile H∞ Controller Designs with Sparse Structures
5. 6.5 Conclusion
14. 7 Non-Fragile H∞ Filtering with Interval-Bounded Coefficient Variations
1. 7.1 Introduction
2. 7.2 Non-Fragile H∞ Filtering for Discrete-Time Systems
3. 7.3 Non-Fragile H∞ Filter Design for Linear Continuous-Time Systems
4. 7.4 Sparse Structured H∞ Filter Design
5. 7.5 Conclusion
15. 8 Insensitive H∞ Filtering of Continuous-Time Systems
1. 8.1 Introduction
2. 8.2 Problem Statement
3. 8.3 Insensitive H∞ Filter Design
4. 8.4 Computation of Robust H∞ Performance Index
5. 8.5 Comparison with the Existing Design Method
6. 8.6 Example
7. 8.7 Conclusion
16. 9 Insensitive H∞ Filtering of Delta Operator Systems
1. 9.1 Introduction
2. 9.2 Problem Statement
3. 9.3 Insensitive H∞ Filter Design
4. 9.4 Example
5. 9.5 Conclusion
17. 10 Insensitive H∞ Output Tracking Control
18. 11 Insensitive H∞ Dynamic Output Feedback Control
1. 11.1 Introduction
2. 11.2 Problem Statement
3. 11.3 Insensitive H∞ Controller Design
4. 11.4 Example
5. 11.5 Conclusion
19. Bibliography
20. Index