Control of a nonlinear magnetic levitation system based RBF neural network

被引：0

作者：

Zhao, Shi-Tie ^{[1
]}

Gao, Xian-Wen ^{[1
]}

Che, Chang-Jie ^{[1
]}

机构：

[1] School of Information Science and Engineering, Northeastern University, Shenyang,110819, China

来源：

Dongbei Daxue Xuebao/Journal of Northeastern University | 2014年 / 35卷 / 12期

关键词：

MATLAB - Controllers - Magnetic levitation - Feedback control - Three term control systems - Adaptive control systems - Magnetic levitation vehicles - Radial basis function networks;

D O I：

10.3969/j.issn.1005-3026.2014.12.001

中图分类号：

学科分类号：

摘要：

Magnetic levitation system is a typical nonlinear and uncertain system, because it must be combined with a controller which has good control performance to be applied in various occasions. The identified nonlinear magnetic levitation system using of the Radial Basis Function neural network (RBFNN) was proposed. The neural network adaptive state feedback controller and adaptive PID controller of magnet levitation system was designed based on the neural network adaptive control principle. Besides, a simulation of the system was proposed by using MATLAB, and the result showed that neural network adaptive controller had a good effect on this nonlinear system. In addition, this control system had a preferable stability and control property. ©, Northeastern University. All right reserved.

引用

页码：1673 / 1676

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