Current Controller for Induction Motor using an Artificial Neural Network trained with a Lyapunov based Algorithm

被引：0

作者：

Viola, Julio ^{[1
]}

Restrepo, Jose ^{[1
,2
]}

Aller, Jose ^{[1
,2
]}

机构：

[1] Univ Politecn Salesiana, Cuenca, Ecuador

[2] Univ Simon Bolivar, Caracas, Venezuela

来源：

2015 IEEE 24TH INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE) | 2015年

关键词：

Backpropagation; Induction motor drives; Lyapunov methods; Neural Networks; ADAPTIVE CONTROL;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents the use of a training algorithm based on a Lyapunov function approach applied to a stator current controller based on a state variable description of the induction machine plus a reference model. The results obtained with the proposed controller are compared with a previously reported method based on a Nonlinear Auto-Regressive Moving Average with eXogenous inputs (NARMAX) description of the induction machine. The proposed Lyapunov based training algorithm is used to ensure convergence of the weights towards a global minimum in the error function. Real time simulations employing a DSP based test bench are used to test the validity of the algorithms and the results are verified by a practical implementation of these controllers.

引用

页码：468 / 475

页数：8

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