A HYDRAULIC ROBOT CONTROLLED BY LEARNING STRUCTURE BASED ON NEURAL NETWORKS

This paper introduces a new kind of backward self-learning control strategy based on the neural networks joined with functional relationship. This control strategy is mainly used to solve problems of the movement control of robot arm with two joints. The simulation and test show that this control strategy is the able to increase the speed of self-adaptation and the starting property of the control system. In order to increase the stability of the control system, ation a series learning scheme is added into the control system and the control system then becomes more stable.