Adaptive Approximation Based Control – Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches: Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
Autor JA Farrellen Limba Engleză Hardback – 22 mai 2006
Din seria Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
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Specificații
ISBN-13: 9780471727880
ISBN-10: 0471727881
Pagini: 440
Dimensiuni: 158 x 241 x 29 mm
Greutate: 0.72 kg
Editura: Wiley
Seria Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
Locul publicării:Hoboken, United States
ISBN-10: 0471727881
Pagini: 440
Dimensiuni: 158 x 241 x 29 mm
Greutate: 0.72 kg
Editura: Wiley
Seria Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
Locul publicării:Hoboken, United States
Public țintă
Dr. Farrell′s approach to Intelligent Control Systems will be of great interest to graduate students studying intelligent control, practitioners, engineers and scientists charged with designing and implementing such systems.Cuprins
Preface.
1. INTRODUCTION.
1.1 Systems and Control Terminology.
1.2 Nonlinear Systems.
1.3 Feedback Control Approaches.
1.4 Components of Approximation Based Control.
1.5 Discussion and Philosophical Comments.
1.6 Exercises and Design Problems.
2. APPROXIMATION THEORY.
2.1 Motivating Example.
2.2 Interpolation.
2.3 Function Approximation.
2.4 Approximator Properties.
2.5 Summary.
2.6 Exercises and Design Problems.
3. APPROXIMATION STRUCTURES.
3.1 Model Types.
3.2 Polynomials.
3.3 Splines.
3.4 Radial Basis Functions.
3.5 Cerebellar Model Articulation Controller.
3.6 Multilayer Perceptron.
3.7 Fuzzy Approximation.
3.8 Wavelets.
3.9 Further Reading.
3.10 Exercises and Design Problems.
4. PARAMETER ESTIMATION METHODS.
4.1 Formulation for Adaptive Approximation.
4.2 Derivation of Parametric Models.
4.3 Design of On-Line Learning Schemes.
4.4 Continuous-Time Parameter Estimation.
4.5 On-Line Learning: Analysis.
4.6 Robust Learning Algorithms.
4.7 Concluding Summary.
4.8 Exercises and Design Problems.
5. NONLINEAR CONTROL ARCHITECTURES.
5.1 Small-Signal Linearization.
5.2 Feedback Linearization.
5.3 Backstepping.
5.4 Robust Nonlinear Control Design Methods.
5.5 Adaptive Nonlinear Control.
5.6 Concluding Summary.
5.7 Exercises and Design Problems.
6. ADAPTIVE APPROXIMATION: MOTIVATION AND ISSUES.
6.1 Perspective for Adaptive Approximation Based Control.
6.2 Stabilization of a Scalar System.
6.3 Adaptive Approximation Based Tracking.
6.4 Nonlinear Parameterized Adaptive Approximation.
6.5 Concluding Summary.
6.6 Exercises and Design Problems.
7. ADAPTIVE APPROXIMATION BASED CONTROL: GENERAL THEORY.
7.1 Problem Formulation.
7.2 Approximation Based Feedback Linearization.
7.3 Approximation Based Backstepping.
7.4 Concluding Summary.
7.5 Exercises and Design Problems.
8. ADAPTIVE APPROXIMATION BASED CONTROL FOR FIXED-WING AIRCRAFT.
8.1 Aircraft Model Introduction.
8.2 Angular Rate Control for Piloted Vehicles.
8.3 Full Control for Autonomous Aircraft.
8.4 Conclusions.
8.5 Aircraft Notation.
Appendix A: Systems and Stability Concepts.
A.1 Systems Concepts.
A.2 Stability Concepts.
A.3 General Results.
A.4 Prefiltering.
A.5 Other Useful Results.
A.6 Problems.
Appendix B: Recommended Implementation and Debugging Approach.
References.
Index.
Descriere
A highly accessible and unified approach to the design and analysis of intelligent control systems Adaptive Approximation Based Control is a tool every control designer should have in his or her control toolbox.