High Precision Prediction of Rolling Force Based on Fuzzy and Nerve Method for Cold Tandem Mill  

作　　者：JIA Chun-yu SHAN Xiu-ying NIU Zhao-ping 

机构地区：[1]College of Mechanical Engineering, Yanshan University, Qinhuangdao 066004, Hebei, China

出　　处：《Journal of Iron and Steel Research International》2008年第2期23-27,共5页

基　　金：Item Sponsored by Natural Science Foundation of Hebei Province of China(E2004000206);National Natural Science Foundation of China(50675186)

摘　　要：The rolling force model for cold tandem mill was put forward by using the Elman dynamic recursive network method,based on the actual measured data.Furthermore,a good assumption is put forward,which brings a full universe of discourse self-adjusting factor fuzzy control,closed-loop adjusting,based on error feedback and expertise into a rolling force prediction model,to modify prediction outputs and improve prediction precision and robustness.The simulated results indicate that the method is highly effective and the prediction precision is better than that of the traditional method.Predicted relative error is less than ±4%,so the prediction is high precise for the cold tandem mill.The rolling force model for cold tandem mill was put forward by using the Elman dynamic recursive network method,based on the actual measured data.Furthermore,a good assumption is put forward,which brings a full universe of discourse self-adjusting factor fuzzy control,closed-loop adjusting,based on error feedback and expertise into a rolling force prediction model,to modify prediction outputs and improve prediction precision and robustness.The simulated results indicate that the method is highly effective and the prediction precision is better than that of the traditional method.Predicted relative error is less than ±4%,so the prediction is high precise for the cold tandem mill.

关 键 词：Elman dynamic recursive network fuzzy control cold tandem mill rolling force PREDICTION 

分 类 号：TG38[金属学及工艺—金属压力加工]