Algorithm Research and Real-time Simulation of Neural Network Sliding Mode Position Control

摘要：

　　This paper presents a neural network sliding mode control algorithm for position control of modular robot.This method adopts BP neural network to approximate the functional relation between the sliding hyperplane and the exponential approximation rate.At the same time,the saturation function of sliding mode control algorithm is replaced by a hyperbolic tangent function to realize the boundary design method of the sliding mode control.The results of real-time simulation show that the algorithm proposed in this paper has the merits of fast response,strong robustness,and reducing the chattering of sliding mode control.This method solves the problems that conventional PID algorithm can’t solve under some circumstances,such as complicated environment,great load change,etc.

关键词： environment great load change etc. Key words:

作者: LI Wei ZHANG Yanyu GAO Yong CHAI Xiuli

作者单位: Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng 475004, China;Schoo School of Automation Science and Engineering, Beihang University, Beijing 100191, China Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng 475004, China

会议类型: 国际会议

会议名称: the 25th Chinese Control and Decision Conference(第25届中国控制与决策会议)

会议地点: 贵阳

会议语种:英文

页码: 1904-1907

在线出版日期: 2013-05-01（万方平台首次上网日期，不代表论文的发表时间）