대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)
- 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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- Pages.657-660
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- 2003
RBF 신경망을 이용한 로봇 매니퓰레이터의 분산제어
Decentralized Control of Robot Manipulator Using the RBF Neural Network
초록
Control of multi-link robot arms is a very difficult problem because of the highly nonlinear dynamics. Decentralized control scheme is developed for control of robot manipulators based on RBF(Radial Basis Function) Neural Networks. RBF Neural Networks is used to approximate the coupling forces among the joints, coriolis force, centrifugal force, gravitational force, and frictional force. The compensation controller is also proposed to estimate the bound of approximation error so that the chattering effect of the control effort can be reduced. The proposed scheme does not require an accurate manipulator dynamic, and it is proved that closed-loop system is asymptotic stable despite the gross robot parameter variations. Numerical simulations for two-link robot manipulator are included to show the effectiveness of controller.