Intelligent control system design for a class of nonlinear mechanical systems

  • Authors:

  • S. Islam;P. X. Liu;A. El Saddik

  • Affiliations:

  • School of Information Technology and Engineering, University of Ottawa, Ottawa, Canada and School of Engineering and Applied Sciences, Harvard University, Cambridge, MA;Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada;School of Information Technology and Engineering, University of Ottawa, Ottawa, Canada

  • Venue:
  • AIS'11 Proceedings of the Second international conference on Autonomous and intelligent systems
  • Year:
  • 2011

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Abstract

In this work, intelligent control technique using multiple parameter models is proposed for robust trajectory tracking control for a class of nonlinear systems. The idea is to reduce the controller gains so as to reduce the control efforts from the single model (SM) certainty equivalence (CE) principle based classical adaptive control approach. The method allows classical adaptive control to be switched into a candidate among the finite set of candidate controllers that best approximates the plant at each instant of time. The Lyapunov function inequality is used to identify a candidate that closely approximates the plant at each instant of time. The design can be employed to achieve good transient tracking performance with smaller values of controller gains in the presence of large scale parametric uncertainties. The proposed design is implemented and evaluated on 3-DOF PhantomPremimum™ 1.5 haptic robot device to demonstrate the effectiveness of the theoretical development.