Reducing computational effort in field optimisation problems
ISSN: 0332-1649
Article publication date: 1 March 2004
Abstract
Design and optimisation of many practical electromechanical devices involve intensive field simulation studies and repetitive usage of time‐consuming software such as finite elements (FEs), finite differences of boundary elements. This is a costly, but unavoidable process and thus a lot of research is currently directed towards finding ways by which the number of necessary function calls could be reduced. New algorithms are being proposed based either on stochastic or deterministic techniques where a compromise is achieved between accuracy and speed of computation. Four different approaches appear to be particularly promising and are summarised in this review paper. The first uses a deterministic algorithm, known as minimal function calls approach, introduces online learning and dynamic weighting. The second technique introduced as ES/DE/MQ – as it combines evolution strategy, differential evolution and multiquadrics interpolation – offers all the advantages of a stochastic method, but with much reduced number of function calls. The third recent method uses neuro‐fuzzy modelling and leads to even further economy of computation, although with slightly reduced accuracy of computation. Finally, a combined FE/neural network approach offers a novel approach to optimisation if a conventional magnetic circuit model could also be used.
Keywords
Citation
Sykulski, J.K. (2004), "Reducing computational effort in field optimisation problems", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 23 No. 1, pp. 159-172. https://doi.org/10.1108/03321640410507626
Publisher
:Emerald Group Publishing Limited
Copyright © 2004, Emerald Group Publishing Limited