| 两自由度闭链机器人的神经网络自适应控制 |
| |
| 引用本文： | 陈正洪,王勇,李艳.两自由度闭链机器人的神经网络自适应控制[J].上海大学学报(英文版),2008,12(5):457-461. |
| |
| 作者姓名： | 陈正洪 王勇 李艳 |
| |
| 基金项目： | 国家自然科学基金，山东省自然科学基金 |
| |
| 摘 要： |
|
| 关 键 词： | 自由度闭链机器人 神经网络 自适应控制 自动控制 |
| 收稿时间： | 2007-03-07 |
| 修稿时间： | 2007-04-02 |
Adaptive proportional integral differential control based on radial basis function neural network identification of a two-degree-of-freedom closed-chain robot |
| |
| CHEN Zheng-hong,WANG Yong,LI Yan.Adaptive proportional integral differential control based on radial basis function neural network identification of a two-degree-of-freedom closed-chain robot[J].Journal of Shanghai University(English Edition),2008,12(5):457-461. |
| |
| Authors: | CHEN Zheng-hong WANG Yong LI Yan |
| |
| Institution: | 1. Department of Engineering Machinery, Shandong Jiaotong University, Jinan 250023, P. R. China;School of Mechanical Engineering, Shandong University, Jinan 250061, P. R. China
2. School of Mechanical Engineering, Shandong University, Jinan 250061, P. R. China |
| |
| Abstract: | A closed-chain robot has several advantages over an open-chain robot, such as high mechanical rigidity, high payload, high precision. Accurate trajectory control of a robot is essential in practical use. This paper presents an adaptive proportional integral differential (PID) control algorithm based on radial basis function (RBF) neural network for trajectory tracking of a two-degree-of-freedom (2-DOF) closed-chain robot. In this scheme, an RBF neural network is used to approximate the unknown nonlinear dynamics of the robot, at the same time, the PID parameters can be adjusted online and the high precision can be obtained. Simulation results show that the control algorithm accurately tracks a 2-DOF closed-chain robot trajectories. The results also indicate that the system robustness and tracking performance are superior to the classic PID method. |
| |
| Keywords: | closed-chain robot radial basis function (RBF) neural network adaptive proportional integral differential (PID) control identification neural network |
| 本文献已被 维普 万方数据 SpringerLink 等数据库收录！ |
| 点击此处可从《上海大学学报(英文版)》浏览原始摘要信息 |
| 点击此处可从《上海大学学报(英文版)》下载免费的PDF全文 |
