基于模糊神经网络的PID张力控制系统.pdfVIP

29 6 Vol . 29 No. 6 2008 6 Journal of Textile Research Jun. 2008 : 0253- 9721 2008) 06- 0109- 04 PID 李 革, 贾元武, 张建新, 赵 匀 , 310018) , PID PID , ) ) ) PID , PID 3 , PID , PID MatLab , PID PID , PID ; ; PID ; :TS 195138 : A Tension control system based on fuzzy- neural network PID LI Ge, JIA Yuanwu, ZHANG Jianxin , ZHAO Yun College of Mechanical andA utomation, Zhejiang Sci-Tech University, Hangzhou , Zhej iang 310018, China) Abstract Since the winding tension control system is a complicated, tandem driving, t ime change and non- linear one, using traditional PID control can not settle the problems of dynamic change of the non- linear system and PID parameter adjustment online. The paper gives one control algorithm ) the combination method of fuzzy-neural network PID control, which can optimize three parameters of PID in operation according to error and error rate at real time, achieve the PID control with the best combinations, and realize the adaptive and intelligent performance of PID control. The fuzzy- neural network PID control is compared with traditional PID by simulat ion through MatLab. The results show that the system has better dynamic, stat ic and adaptive performances by using the fuzzy- neural network PID control strategy. Key words tension control; fuzzy- neural network ; PID control; simulation , , , [ 1- 2] , , , , ) ) ) , , , , , , , , , , , 1 , 111