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Multiple Models Approach in Automation : Takagi-Sugeno Fuzzy Systems.
Annotation
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken :
Wiley-ISTE [Imprint], John Wiley & Sons, Incorporated.
Dec. 2012 ;
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| Colección: | Iste Ser.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- A1.2.1. Open left half-planeA1.2.2. [alpha]-stability; A1.2.3. Vertical band; A1.2.4. Horizontal band; A1.2.5. Disk of radius R, centered at (q,0); A1.2.6. Conical sector.; Appendix 2: Properties of M-Matrices; Appendix 3: Stability and Comparison Systems; A3.1. Vector norms and overvaluing systems; A3.1.1. Definition of a vector norm; A3.1.2. Definition of a system overvalued from a continuous process; A3.1.3. Application; A3.2. Vector norms and the principle of comparison; A3.3. Application to stability analysis; Bibliography; Index.
- Title Page; Contents; Notations; Introduction; Chapter 1. Multiple Model Representation; 1.1. Introduction; 1.2. Techniques for obtaining multiple models; 1.2.1. Construction of multiple models by identification; 1.2.2. Multiple model construction by linearization; 1.2.3. Multiple model construction by mathematical transformation; 1.2.4. Multiple model representation using the neural approach; 1.3. Analysis and synthesis tools; 1.3.1. Lyapunov approach; 1.3.2. Numeric tools: linear matrix inequalities; 1.3.3. Multiple model control techniques.
- Chapter 2. Stability of Continuous Multiple Models2.1. Introduction; 2.2. Stability analysis; 2.2.1. Exponential stability; 2.3. Relaxed stability; 2.4. Example; 2.5. Robust stability; 2.5.1. Norm-bounded uncertainties; 2.5.2. Structured parametric uncertainties; 2.5.3. Analysis of nominal stability; 2.5.4. Analysis of robust stability; 2.6. Conclusion; Chapter 3. Multiple Model State Estimation; 3.1. Introduction; 3.2. Synthesis of multiple observers; 3.2.1. Linearization; 3.2.2. Pole placement; 3.2.3. Application: asynchronous machine; 3.2.4. Synthesis of multiple observers.
- 3.3. Multiple observer for an uncertain multiple model3.4. Synthesis of unknown input observers; 3.4.1. Unknown inputs affecting system state; 3.4.2. Unknown inputs affecting system state and output; 3.4.3. Estimation of unknown inputs; 3.5. Synthesis of unknown input observers: another approach; 3.5.1. Principle; 3.5.2. Multiple observers subject to unknown inputs and uncertainties; 3.6. Conclusion; Chapter 4. Stabilization of Multiple Models; 4.1. Introduction; 4.2. Full state feedback control; 4.2.1. Linearization; 4.2.2. Specific case; 4.2.3. [alpha]-stability: decay rate.
- 4.3. Observer-based controller4.3.1. Unmeasurable decision variables; 4.4. Static output feedback control; 4.4.1. Pole placement; 4.5. Conclusion; Chapter 5. Robust Stabilization of Multiple Models; 5.1. Introduction; 5.2. State feedback control.; 5.2.1. Norm-bounded uncertainties; 5.2.2. Interval uncertainties; 5.3. Output feedback control; 5.3.1. Norm-bounded uncertainties; 5.3.2. Interval uncertainties; 5.4. Observer-based control; 5.5. Conclusion; Conclusion; APPENDICES; Appendix 1: LMI Regions; A1.1. Definition of an LMI region; A1.2. Interesting LMI region examples.