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Review and Discussion on Model Reference Adaptive Control for Mechanical Mechanisms

[+] Author Affiliations
Dan Zhang, Bin Wei

York University, Toronto, ON, Canada

Paper No. DETC2017-67378, pp. V006T10A010; 10 pages
doi:10.1115/DETC2017-67378
From:
  • ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 6: 13th International Conference on Multibody Systems, Nonlinear Dynamics, and Control
  • Cleveland, Ohio, USA, August 6–9, 2017
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5820-2
  • Copyright © 2017 by ASME

abstract

Traditional control systems are not able to properly balance out the load variation impact when robotic mechanisms carry and transport a variety of payloads. Adaptive control, particularly the model reference adaptive control (MRAC), is one of the ideal solutions that one can resort to address the mentioned problem. Adaptive control can be categorized into the following, model reference, self-tuning and gain-scheduled. Here, the authors mainly focus on the MRAC category. To the best of the authors’ knowledge, not so many recent papers can be found on MRAC for robotic manipulators because robotic manipulators are usually highly nonlinear and coupled systems, and sometimes it is not easy to design a stable MRAC in the robotic systems. This paper reviews and discusses the MRAC that is used in robotic manipulators and some issues of MRAC for robotic manipulators are presented as well. This review is able to give a general guideline for the future research in the MRAC of robotic manipulators.

Copyright © 2017 by ASME

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