Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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Design of Combined Direct/Indirect Adaptive Neural Control System using Fuzzy Rule

퍼지규칙에 의한 직/간접 혼합 신경망 적응제어시스템의 설계

  • Jang, Soon-Ryong (School of Electrical Engineering, Gyeongsang National University) ;
  • Choi, Jae-Seok (School of Electrical Engineering, Gyeongsang National University) ;
  • Lee, Soon-Young (School of Electrical Engineering, Gyeongsang National University)
  • 장순용 (경상대학교 전기전자공학부) ;
  • 최재석 (경상대학교 전기전자공학부) ;
  • 이순영 (경상대학교 전기전자공학부)
  • Published : 1999.07.19
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Abstract

In this paper, the direct and indirect neural adaptive controller are combined based on the Lyapunov synthesis approach. The proposed adaptive controller is constructed from RBF neural network and a set of fuzzy IF-THEN rules. And the weighting parameters are adjusted on-line according to some adaptation law for the purpose of controlling the plant to track a given trajectory. In this scheme, fuzzy IF-THEN rules are used to decide the combined weighting factor. It is shown that all the signals in the closed-loop system are uniformly bounded under mild assumptions. The effectiveness of the proposed control scheme is demonstrated through the control of one-link rigid robotics manipulator.

Keywords