대한전기학회논문지:시스템및제어부문D (The Transactions of the Korean Institute of Electrical Engineers D)

대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지

RBFN를 이용한 로봇 매니퓰레이터의 신경망 적응 제어

Neuro-Adaptive Control of Robot Manipulator Using RBFN

  • 김정대 ((주)코웰 시스넷 개발부) ;
  • 이민중 (부산대 전기공학과) ;
  • 최영규 (부산대 전자전기정보컴퓨터공학부) ;
  • 김성신 (부산대 전기전자정보컴퓨터공학부)
  • 발행 : 2001.01.01
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초록

This paper investigates the direct adaptive control of nonlinear systems using RBFN(radial basis function networks). The structure of the controller consists of a fixed PD controller and a RBFN controller in parallel. An adaptation law for the parameters of RBFN is developed based on the Lyapunov stability theory to guarantee the stability of the overall control system. The filtered tracking error between the system output and the desired output is shown to be UUB(uniformly ultimately bounded). To evaluate the performance of the controller, the proposed method is applied to the trajectory contro of the two-link manipulator.

키워드

참고문헌

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