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The optimisation of electromagnetic devices using a combined finite element/neural network approach with on‐line training

J. Seguin (Electrical and Computer Engineering Department, McGill University, Montreal, Quebec, Canada, and)
F. Dandurand (Electrical and Computer Engineering Department, McGill University, Montreal, Quebec, Canada, and)
D.A. Lowther (Electrical and Computer Engineering Department, McGill University, Montreal, Quebec, Canada, and)
J.K. Sykulski (Electrical Engineering Department, Southampton University, Southampton, UK)
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Abstract

The paper presents a novel method of utilising neural networks for optimisation systems. First, a conventional magnetic circuit model of the device is developed to create a set of sensitivity rules which guide the optimisation. The rules are coded in a knowledge‐based neural network. Second, an error network is developed to correct the approximations inherent in the magnetic circuit approach and this combines with the first network to generate realistic outputs. Finally, the error network can be trained on‐line with a finite element system. Over time, the network replaces the finite element analysis, thus speeding up the optimisation process.

Keywords

Citation

Seguin, J., Dandurand, F., Lowther, D.A. and Sykulski, J.K. (1999), "The optimisation of electromagnetic devices using a combined finite element/neural network approach with on‐line training", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 18 No. 3, pp. 266-274. https://doi.org/10.1108/03321649910274801

Publisher

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MCB UP Ltd

Copyright © 1999, MCB UP Limited

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