Learning-Based Adaptive Control
eBook - ePub

Learning-Based Adaptive Control

An Extremum Seeking Approach – Theory and Applications

  1. 282 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Learning-Based Adaptive Control

An Extremum Seeking Approach – Theory and Applications

About this book

Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained. - Includes a good number of Mechatronics Examples of the techniques. - Compares and blends Model-free and Model-based learning algorithms. - Covers fundamental concepts, state-of-the-art research, necessary tools for modeling, and control.

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Yes, you can access Learning-Based Adaptive Control by Mouhacine Benosman in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Preface
  6. Acknowledgments
  7. Chapter 1: Some Mathematical Tools
  8. Chapter 2: Adaptive Control: An Overview
  9. Chapter 3: Extremum Seeking-Based Iterative Feedback Gains Tuning Theory
  10. Chapter 4: Extremum Seeking-Based Indirect Adaptive Control
  11. Chapter 5: Extremum Seeking-Based Real-Time Parametric Identification for Nonlinear Systems
  12. Chapter 6: Extremum Seeking-Based Iterative Learning Model Predictive Control (ESILC-MPC)
  13. Conclusions and Further Notes
  14. Index