Describing complex concepts with a variety of theoretical and practical illustrations, this book also:
- Develops a comprehensive set of performance based adaptive control results
- Provides a constructive framework for estimating both upper and lower bounds of performance cost functionals
- Presents theoretical principles and a mathematically well–founded introduction to the area of ′intelligent control′
Featuring a toolkit that allows quantitative comparisons between competing control designs, Performance of Nonlinear Approximate Adaptive Controllers will prove an invaluable reference for control practitioners and theorists, AI researchers, applied mathematicians and graduate students in adaptive control and stability.
Introduction.
Approximation Theory.
Uncertainty Modelling, Control Design and System Performance.
The Chain of Integrators.
Function Approximator Designs for the Integrator Chain.
Resolution Divergence.
Resolution Scaling.
Strict Feedback Systems.
Output Feedback Control.
Comparison to Alternative Designs.
Conclusions and Outlook.
Appendix A: Lyapunov′s Direct Method.
Appendix B: Functional Bounds from System Identification.
References.
Index.
Csaba Szepesvári
Eric Rogers