Learning-based Adaptive Control: An Extremum Seeking Approach Theory And Applications by Mouhacine BenosmanLearning-based Adaptive Control: An Extremum Seeking Approach Theory And Applications by Mouhacine Benosman

Learning-based Adaptive Control: An Extremum Seeking Approach Theory And Applications

byMouhacine Benosman

Paperback | July 11, 2016

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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.
Mouhacine Benosman worked at universities in Rome, Italy, Reims, France, and Glasgow, Scotland before spending 5 years as a Research Scientist with the Temasek Laboratories at the National University of Singapore.He is presently senior researcher at the Mitsubishi Electric Research Laboratories (MERL), Cambridge, USA. His research inte...
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Title:Learning-based Adaptive Control: An Extremum Seeking Approach Theory And ApplicationsFormat:PaperbackDimensions:282 pages, 8.75 × 6.35 × 0.68 inPublished:July 11, 2016Publisher:Butterworth (trade)Language:English

The following ISBNs are associated with this title:

ISBN - 10:0128031360

ISBN - 13:9780128031360

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Table of Contents

Chapter 1: Some Mathematical Tools

Chapter 2: Adaptive Control: An Overview

Chapter 3: Extremum Seeking-Based Iterative Feedback Gains Tuning Theory

Chapter 4: Extremum Seeking-Based Indirect Adaptive Control

Chapter 5: Extremum Seeking-Based Real-Time Parametric Identification for Nonlinear Systems

Chapter 6: Extremum Seeking-Based Iterative Learning Model Predictive Control (ESILC-MPC)