신경 회로망을 이용한 로보트 매니퓰레이터의 Hybrid 위치/힘 제어기의 설계

Hybrid position/force controller design of the robot manipulator using neural network

In this paper ,ie propose a hybrid position/force controller of a robot manipulator using double-layer neural network. Each layer is constructed from inverse dynamics and Jacobian transpose matrix, respectively. The weighting value of each neuron is trained by using a feedback force as an error signal. If the neural networks are sufficiently trained it does not require the feedback-loop with error signals. The effectiveness of the proposed hybrid position/force controller is demonstrated by computer simulation using a PUMA 560 manipulator.