QFT Parameter-Scheduling Control Design for Linear Time- varying Systems Based on RBF Networks

  • Park, Jae-Weon (School of Mechanical Engineering and Research Institute of mechanical Technology Pusan National University) ;
  • Yoo, Wan-Suk (School of Mechanical Engineering and Research Institute of mechanical Technology Pusan National University) ;
  • Lee, Suk (School of Mechanical Engineering and Research Institute of mechanical Technology Pusan National University) ;
  • Im, Ki-Hong (School of Electrical Engineering and Computer Science, Seoul National University) ;
  • Park, Jin-Young (School of Electrical Engineering and Computer Science, Seoul National University)
  • Published : 2003.04.01

Abstract

For most of linear time-varying (LTV) systems, it is difficult to design time-varying controllers in analytic way. Accordingly, by approximating LTV systems as uncertain linear time-invariant, control design approaches such as robust control have been applied to the resulting uncertain LTI systems. In particular, a robust control method such as quantitative feedback theory (QFT) has an advantage of guaranteeing the frozen-time stability and the performance specification against plant parameter uncertainties. However, if these methods are applied to the approximated linear. time-invariant (LTI) plants with large uncertainty, the resulting control law becomes complicated and also may not become ineffective with faster dynamic behavior. In this paper, as a method to enhance the fast dynamic performance of LTV systems with bounded time-varying parameters, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks.

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