Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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A design of neuro-fuzzy adaptive controller using a reference model following function

기준 모델 추종 기능을 이용한 뉴로-퍼지 적응 제어기 설계

  • 이영석 (영진전문대학 전기과) ;
  • 유동완 (경북대학교 대학원 전기공학과) ;
  • 서보혁 (경북대학교 전자.전기공학부)
  • Published : 1998.04.01
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Abstract

This paper presents an adaptive fuzzy controller using an neural network and adaptation algorithm. Reference-model following neuro-fuzzy controller(RMFNFC) is invesgated in order to overcome the difficulty of rule selecting and defects of the membership function in the general fuzzy logic controller(FLC). RMFNFC is developed to tune various parameter of the fuzzy controller which is used for the discrete nonlinear system control. RMFNFC is trained with the identification information and control closed loop error. A closed loop error is used for design criteria of a fuzzy controller which characterizes and quantize the control performance required in the overall control system. A control system is trained up the controller with the variation of the system obtained from the identifier and closed loop error. Numerical examples are presented to control of the discrete nonlinear system. Simulation results show the effectiveness of the proposed controller.

Keywords

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