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Learning-Based Adaptive Control: An Extremum Seeking Approach – Theory and Applications

Autor Mouhacine Benosman
en Limba Engleză Paperback – 11 iul 2016
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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Specificații

ISBN-13: 9780128031360
ISBN-10: 0128031360
Pagini: 282
Dimensiuni: 151 x 229 x 18 mm
Greutate: 0.44 kg
Editura: ELSEVIER SCIENCE

Cuprins

1. Some Mathematical Tools 2. Adaptive Control: An Overview 3. Extremum Seeking-Based Iterative Feedback Gains Tuning Theory 4. Extremum Seeking-Based Indirect Adaptive Control 5. Extremum Seeking-Based Real-Time Parametric Identification for Nonlinear Systems 6. Extremum Seeking-Based Iterative Learning Model Predictive Control (ESILC-MPC)