一种液压驱动机械手的神经网络学习控制结构

A HYDRAULIC ROBOT CONTROLLED BY LEARNINGSTRUCTURE BASED ON NEURAL NETWORKS

针对二自由度机械手的控制问题，本文提出了一种基于函数联接神经网络的反馈学习控制器，提高了控制系统的自适应速度，改善了系统的起始特性．为了在改善系统自适应速度的同时增强系统的稳态特性，本文又提出了基于函数联接神经网络的串级学习控制算法．仿真和实验都证明了控制方法的优越性．

This paper introduces a new kind of backward selflearning 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 selfadaptation 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.