Title :
Neural network for roller gap setup in rolling steel mill
Author :
Cui, Jianjiang ; Xiao, Wendong ; Xu, Xinhe ; Wu, Wenbm
Author_Institution :
Control & Simulation Center, Northeastern Univ., Shenyang, China
Abstract :
In this paper the methods to control steel strip thickness setup are analyzed for rolling process. By considering many factors that influence the steel strip thickness accuracy, the final thickness error functional formula is obtained. A BP neural network prediction model of final thickness error is presented, high order algorithm is adopted. We train the neural network according to steel strip classification. The combination of this model with others enhances greatly thickness accuracy control
Keywords :
backpropagation; neural nets; process control; rolling; steel industry; thickness control; BP neural network prediction model; backpropagation; high-order algorithm; roller gap setup; rolling process; rolling steel mill; steel strip classification; steel strip thickness; steel strip thickness setup control; thickness accuracy control; thickness error functional formula; Automatic control; Feedback control; Intelligent networks; Milling machines; Neural networks; Predictive models; Slabs; Steel; Strips; Thickness control;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.863418
