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A Neural Network Based Adaptive Tracking Controller for Nonholonomic Wheeled Mobile Robots With Unknown Dynamics

[+] Author Affiliations
Omid Mohareri

Simon Fraser University, Vancouver, BC, Canada

Rached Dhaouadi

American University of Sharjah, Sharjah, UAE

Paper No. IMECE2010-40856, pp. 827-834; 8 pages
doi:10.1115/IMECE2010-40856
From:
  • ASME 2010 International Mechanical Engineering Congress and Exposition
  • Volume 8: Dynamic Systems and Control, Parts A and B
  • Vancouver, British Columbia, Canada, November 12–18, 2010
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4445-8
  • Copyright © 2010 by ASME

abstract

This paper presents the design, implementation and comparative analysis of an intelligent neural network based controller used for adaptive trajectory tracking of a wheeled mobile robot with unknown dynamics. In this proposed control scheme, the neural network is used to continuously tune the gains of the kinematic based controller in a backstepping structure. The online learning and adaptive capabilities of the neural network are utilized to achieve a smooth and fast robot tracking motion. The simulation results are used to verify the tracking performance of the proposed control algorithm and to compare it with the conventional backstepping controller.

Copyright © 2010 by ASME

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