Open AccessIdentification and Control of Elongation System of Skin Passing Mill Based on Intelligent Algorithm
Author(s) -
Xiuyan Ren,
H. Oliver Gao,
Huibin Xu,
Huagui Huang,
Jining Sun
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1820/1/012154
Subject(s) - control theory (sociology) , pid controller , robustness (evolution) , overshoot (microwave communication) , mill , nonlinear system , control system , control engineering , elongation , fuzzy logic , artificial neural network , computer science , function (biology) , engineering , control (management) , artificial intelligence , temperature control , materials science , chemistry , ultimate tensile strength , biology , telecommunications , biochemistry , quantum mechanics , evolutionary biology , metallurgy , mechanical engineering , physics , electrical engineering , gene
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.