Neural network simulation of a pulse magnetiser for magnetising permanent magnets

被引：0

作者：

Rudnicki, M ^{[1
]}

Neittaanmäki, P

Jokinen, T

机构：

[1] Inst Elect Engn, Dept Small Elect Machines, Warsaw, Poland

[2] Univ Jyvaskyla, Dept Math, SF-40100 Jyvaskyla, Finland

[3] Aalto Univ, Lab Electromech, FIN-02150 Espoo, Finland

来源：

COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING | 1998年 / 17卷 / 5-6期

关键词：

global optimization; neural networks; neurocontroller; permanent magnets; pulse;

D O I：

10.1108/03321649810221242

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The paper is concerned with a design and a validation of a neurocontroller for a pulse magnetiser for magnetising permanent magnets. The goal is to register the peak time and crest current in order to pick up an optimal intermittent duty conditions regime for the magnetiser. This is usually done by solving a set of coupled ordinary differential equations describing current waveforms and the temperature rise in the magnetising winding. The neurocontroller is based on a one-layer feedforward neural network which is trained using the Levenberg-Marquardt learning rule. We present the results produced by the neurocontroller and we compare them with the numerical and measurement results. The neurocontroller is intended to serve later as a part of a global optimising algorithm.

引用

页码：697 / +

页数：13

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