Title :
Coiling eccentricity compensation control system based on BP Neural Network Algorithm
Author :
Sun, Wenquan ; Shao, Jian ; He, Anrui ; Yang, Quan ; Guan, Jianlong
Author_Institution :
Nat. Eng. Res. Center for Adv. Rolling Technol., Univ. of Sci. & Technol. Beijing, Beijing, China
Abstract :
This paper proposes the eccentric problem in the coiling process. The BP Neural Network Algorithm compensation control method is designed: A BP Neural Network multi-resolution controller is introduced in the control cycle of coiling tension control, the purpose of the controller is to reduce the influence of coiling eccentricity on tension, thickness and flatness of strip. The simulation result approves that the method is effective to improve the coiling tension control precision.
Keywords :
backpropagation; compensation; neurocontrollers; rolling; BP neural network algorithm compensation control method; BP neural network multiresolution controller; coiling eccentricity compensation control system; coiling process; coiling tension control; control cycle; eccentric problem; Biological neural networks; Coils; Fluctuations; Neurons; Process control; Strips; Training; Neural Network Algorithm; coiling eccentricity; cold rolling; eccentricity compensation method;
Conference_Titel :
Electronics, Communications and Control (ICECC), 2011 International Conference on
Conference_Location :
Ningbo
Print_ISBN :
978-1-4577-0320-1
DOI :
10.1109/ICECC.2011.6066538
