제어로봇시스템학회:학술대회논문집
- 1990.10a
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- Pages.7-12
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- 1990
Variable structure control of robot manipulator using neural network
신경 회로망을 이용한 가변 구조 로보트 제어
Abstract
In this paper, we propose a new manipulator control scheme based on the CMAG neural network. The proposed control consists of two components. The feedforward component is an output of trained CMAC neural network and the feedback component is a modified sliding mode control. The CMAC accepts the position, velocity and acceleration of manipulator as input and outputs two values for the controller : One is the nominal torque used for feedforward compensation(M1 network) and the other is the inertia matrix related information used for the feedback component(M2 network). Since the used control algorithm guarantees the robust trajectory tracking in spite of modeling errors, the CMAC mapping errors due to the memory limitation are little worth consideration.
Keywords