Multiple Models Approach in Automation: Takagi-Sugeno Fuzzy Systems

Table of contents

1. Cover
2. Contents
3. Title page
4. Copyright page
5. Notations
6. Introduction
7. Chapter 1: Multiple Model Representation
   1. 1.1. Introduction
   2. 1.2. Techniques for obtaining multiple models
   3. 1.3. Analysis and synthesis tools
8. Chapter 2: Stability of Continuous Multiple Models
   1. 2.1. Introduction
   2. 2.2. Stability analysis
   3. 2.3. Relaxed stability
   4. 2.4. Example
   5. 2.5. Robust stability
   6. 2.6. Conclusion
9. Chapter 3: Multiple Model State Estimation
   1. 3.1. Introduction
   2. 3.2. Synthesis of multiple observers
   3. 3.3. Multiple observer for an uncertain multiple model
   4. 3.4. Synthesis of unknown input observers
   5. 3.5. Synthesis of unknown input observers: another approach
   6. 3.6. Conclusion
10. Chapter 4: Stabilization of Multiple Models
    1. 4.1. Introduction
    2. 4.2. Full state feedback control
    3. 4.3. Observer-based controller
    4. 4.4. Static output feedback control
    5. 4.5. Conclusion
11. Chapter 5: Robust Stabilization of Multiple Models
    1. 5.1. Introduction
    2. 5.2. State feedback control
    3. 5.3. Output feedback control
    4. 5.4. Observer-based control
    5. 5.5. Conclusion
12. Conclusion
13. APPENDICES
    1. Appendix 1: LMI Regions
       1. A1.1. Definition of an LMI region
       2. A1.2. Interesting LMI region examples
    2. Appendix 2: Properties of M-Matrices
    3. Appendix 3: Stability and Comparison Systems
       1. A3.1. Vector norms and overvaluing systems
       2. A3.2. Vector norms and the principle of comparison
       3. A3.3. Application to stability analysis
14. Bibliography
15. Index