- RBFN를 이용한 로봇 매니퓰레이터의 신경망 적응 제어
- ㆍ 저자명
- 김정대,이민중,최영규,김성신
- ㆍ 간행물명
- 전기학회논문지. The transactions of the Korean Institute of Electrical Engineers. D / D, 시스템 및 제어부문
- ㆍ 권/호정보
- 2001년|50권 1호|pp.38-44 (7 pages)
- ㆍ 발행정보
- 대한전기학회
- ㆍ 파일정보
- 정기간행물| PDF텍스트
- ㆍ 주제분야
- 기타
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.