Identification and Control of Elongation System of Skin Passing Mill Based on Intelligent Algorithm

• Published in: Journal of physics. Conference series Vol. 1820; no. 1; p. 12154
• Main Authors: Ren, Xin-Yi, Gao, Hui-Min, Xu, Hai-Wei, Huang, Hua-Gui, Sun, Jing-Na
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.03.2021
• Subjects: Algorithms; Control methods; Control systems; Elongation; Fuzzy control; Fuzzy logic; Immune system; Neural networks; Parameter identification; Physics; Proportional integral derivative; Robust control
• DOI: 10.1088/1742-6596/1820/1/012154
• ISSN: 1742-6588

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.