Abstract

In view of the nonlinear, time-varying and time-delay characteristics of elongation control system of skin pass mill, according to analysis of the mechanism model of elongation control system of skin pass mill, BP neural network was used to identify the structural parameters of the model. With reference to the regulating function of biological immune system and the function of fuzzy reasoning logic which can approach nonlinear function, a fuzzy immune PID control strategy was proposed to improve the elongation control accuracy of skin pass mill combining fuzzy control and immune feedback mechanism with traditional PID control. The simulation results show that the control strategy has the advantages of small overshoot, fast response, strong anti-interference ability and robustness, and the control effect is better than the traditional control method.

Details

Title
Identification and Control of Elongation System of Skin Passing Mill Based on Intelligent Algorithm
Author
Xin-Yi, Ren 1 ; Hui-Min, Gao 1 ; Hai-Wei, Xu 1 ; Hua-Gui, Huang 2 ; Jing-Na, Sun 2 

 (Technology Center, Shougang Jingtang Iron and Steel Co., Ltd, Tangshan 063200, China 
 National Engineering Research Center for Equipment and Technology of Cold Rolling, Yanshan University, Qinhuangdao 066004, China 
Publication year
2021
Publication date
Mar 2021
Publisher
IOP Publishing
ISSN
17426588
e-ISSN
17426596
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2512939629
Copyright
© 2021. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.