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

fYear

2011

fDate

9-11 Sept. 2011

Firstpage

1945

Lastpage

1950

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Communications and Control (ICECC), 2011 International Conference on

Conference_Location

Ningbo

Print_ISBN

978-1-4577-0320-1

Type

conf

DOI

10.1109/ICECC.2011.6066538

Filename

6066538