Research on Loop Decoupling Control Based on Fuzzy RBF Neural Network

被引：0

作者：

Li, Boqun ^{[1
]}

Wang, Lin ^{[1
]}

Zhang, ShengLin ^{[1
]}

Wang, Junjie ^{[1
]}

机构：

[1] Univ Sci & Technol Liaoning, Sch Elect & Informat Engn, Ahshan 114051, Peoples R China

来源：

PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021) | 2021年

关键词：

Looper System; Decoupling; Fuzzy RBF Neural Network; PID Control;

D O I：

10.1109/CCDC52312.2021.9602369

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In hot strip rolling mill, looper system is multivariable, strongly coupled and highly disturbed. These characteristics make the design of multivariable loop system more complex. For this complex nonlinear system, the mathematical model of looper system is established. Due to the better convergence performance of fuzzy control and the self-learning and self-adaptive characteristics of neural network, the conventional PID control is combined with fuzzy control and neural network. A PID control method based on fuzzy radial basis function (RBF) neural network is proposed to decouple the looper system. Through MATLAB simulation, the results show that the decoupling control method has good decoupling effect, fast response speed, good anti-interference performance, and effectively improves the control accuracy of looper system.

引用

页码：4989 / 4994

页数：6

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