Performance.Of.Nonlinear.Approximate.Adaptive.Controllers

Description

In recent years there has been a wide interest in non-linear adaptive control using approximate models, either for tracking or regulation, and usually under the banner of neural network based control. The authors present a unique critical evaluation of the approximate model philosophy and its setting, rigorously comparing the performance of such controls against competing designs. Analysing a very topical aspect of contemporary research and control practice this book highlights the situations in which approximate model based designs are most appropriate and indicates scenarios in which other designs could be used more productively. Throughout the text concepts are illustrated using a variety of examples, both academic problems and those based on physical examples. The work is designed to open the door to realistic applications.
Unified coverage of the theory and application of a wide range of control systems areas including neural network based control and control using the approximate model
Presents a mathematically well founded introduction to the area of intelligent control
A varied selecion of practical examples drawn from a variety of fields, including robotics and aerospace, illustrate theoretical principles
Clear compaisons of a variety of control designs
Cross disciplinary approach to this leading edge topic
A valuable reference for control practitioners and theorists, artificial intelligence researchers and applied mathematicians, as well as graduate students and researchers with an interest in adaptive control and stability.

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1. Ebooks list page : 296
2. Performance Of Nonlinear Approximate Adaptive Controllers
3. Performance of Nonlinear Approximate Adaptive Controllers
4. Performance of Nonlinear Approximate Adaptive Controllers
5. Approximate and Renormgroup Symmetries (Nonlinear Physical Science)
6. Nonlinear and Adaptive Control with Applications
7. Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches
8. Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches
9. Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches
10. Multiscale, Nonlinear and Adaptive Approximation: Dedicated to Wolfgang Dahmen on the Occasion of his 60th Birthday
11. Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models
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14. Extending H-infinity Control to Nonlinear Systems: Control of Nonlinear Systems to Achieve Performance Objectives
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