로봇 매니퓰레이터의 퍼지논리 제어를 위한 신경회로망을 사용한 규칙 베이스 유도방법

We propose a control architecture for the fuzzy logic control of robot manipulators and a rule base derivation method for a fuzzy logic controller( FLC ) using a neural network. The control architecture is composed of FLC and PD( Positional Derivative ) controller. And a neural network is designed in consideration of the FLC's structure. After the training is finished by BP( Back Propagation ) and FEL( Feedback Error Learning ) method, the rule base is derived from the neural network and is reduced through two stages - smoothing, logical reduction. Also, we show the performance of the control architecture through the simulation to verify the effectiveness of our proposed method.