期刊名称：International Journal of Future Generation Communication and Networking
印刷版ISSN：2233-7857
出版年度：2013
卷号：6
期号：4
出版社：SERSC
摘要：In this paper, a parameters self-learning PID controller algorithm based on modified BP neural network is proposed to eliminate the influence of time delay on the stability and maneuverability of tele-operation manipulators. This control algorithm adjusts the three parameters of PID controller on line through BP neural network. Conjugate gradient method is used for real-time adjustment of weighted coefficient of BP neural network so as to adjust the output parameter of PID controller. The model of three-joint manipulator with three degrees of freedom (3-DOF) was established. The simulation results show that force tracking performance of master and slave manipulators is good, the maximum error is 0.15. The position tracking performance of slave manipulator is stable, the amplitude decay can be ignored, the maximum error is 3.9 and time delay is 0.3s. This control algorithm has fine self-learning capability and robustness. It had better time delay control effect and could improve the operability of internet-based tele-operation manipulators.
关键词：Internet-based tele-operation; Time delay; Manipulator; Neural network PID control
