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

Informationen zum Autor 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 interests include modelling and control of flexible systems, non-linear robust and fault tolerant control, vibration suppression in industrial machines, multi-agent control with applications to smart-grid, and more recently his research focus is on learning and adaptive control with application to mechatronics systems. The author has published more than 40 peer-reviewed journals and conferences, and more than 10 patents in the field of mechatronics systems control. He is a senior member of the IEEE society and an Associate Editor of the Control System Society Conference Editorial Board.

List of contents

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)

Product details

• Authors: Mouhacine Benosman, Benosman Mouhacine
• Publisher: ELSEVIER SCIENCE BV
• Languages: English
• Product format: Paperback / Softback
• Released: 31.07.2016
• EAN: 9780128031360
• ISBN: 978-0-12-803136-0
• No. of pages: 282
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; machine learning, Artificial Intelligence, TECHNOLOGY & ENGINEERING / Mechanical, Mechanical Engineering, COMPUTERS / Artificial Intelligence / General