Digital Control of Servo Systems Using Neural Networks. A Method of Off-Line Learning.

Abstract

When neural networks are applied to servo systems, the computation time of the control algorithms cannot be neglected, and the time period of on-line learning is expected to be shortened, considering the life span of the plant and the saving of electric energy. In this paper, we first proposed a design method of digital control systems using neural networks. In this method, the future information of the desired value is used as the input of the neural network and the computation time of the control algorithm is taken into account. Secondly, we presented an off-line learning method based on an approximate model of the servo system. The effectiveness of the proposed control systems and the off-line learning method is demonstrated by experiments and simulations on the control of a parallelogram link robot manipulator of 2 degrees of freedom.