摘要
提出一种神经网络与PD并行控制的机器人学习控制系统。为了加快神经网络的学习算法,在数字复合正交神经网络的基础上给出一种模拟复合正交神经网络的学习算法,以两关节机器人为对象仿真结果表明,该控制方法使机器人跟踪期望轨迹,其系统响应、跟踪精度和鲁棒性优于常规的控制方法,位置跟踪获得了满意的控制效果。该模拟神经控制器为不确定系统的控制提供了一种新的途径。
A learning control system of robots with the parallel control of neural network and PD is presented in this paper.A learning algorithm for analog compound orthogonal neural network is given on the basis of the digital compound orthogonal neural network to obtain a high speed-learning algorithm.The simulation results of the robot manipulator with two joints prove that in the tracking desired path lines of the robot,the control method is superior to the conventional control methods in system responses,tracking accuracy,and robustness.The position tracking control obtains satisfactory effectiveness.The analog neural controller provides a novel approach for uncertain control systems.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第7期208-210,214,共4页
Computer Engineering and Applications
基金
浙江省自然科学基金(the Natural Science Foundation of Zhejiang Province of China under Grant No.M603070)
关键词
模拟复合正交神经网络
机器人
并行控制
analog compound orthogonal neural network
robot manipulator
parallel control
