Solution of Jiles-Atherton vector hysteresis parameters estimation by modified Differential Evolution approaches

Authors:
Leandro dos Santos Coelho;Viviana Cocco Mariani;Jean Vianei Leite
Affiliations:
Industrial and Systems Engineering Graduate Program, PPGEPS, Pontifical Catholic University of Parana, PUCPR, Imaculada Conceição, 1155, Zip Code 80215-901, Curitiba, Parana, Brazil;Department of Mechanical Engineering, Pontifical Catholic University of Parana, PUCPR, Imaculada Conceição, 1155, Zip Code 80215-901, Curitiba, Parana, Brazil;Department of Electrical Engineering, GRUCAD, Federal University of Santa Catarina, UFSC, Postal Box 476, Zip code 88040-970, Florianopolis, Santa Catarina, Brazil
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

Differential Evolution (DE) is a simple and efficient stochastic global optimization algorithm of evolutionary computation field, which involves the evolution of a population of solutions using operators such as mutation, crossover, and selection. The basic idea of DE is to adapt the search during the evolutionary process. At the start of the evolution, the perturbations are large since parent populations are far away from each other. As the evolutionary process matures, the population converges to a small region and the perturbations adaptively become small. DE approaches have been successfully applied to solve a wide range of optimization problems. In this paper, the parameters set of the Jiles-Atherton vector hysteresis model is obtained with an approach based on modified Differential Evolution (MDE) approaches using generation-varying control parameters based on generation of random numbers with uniform distribution. Several evaluated MDE approaches perform better than the classical DE methods and a genetic algorithm approach in terms of the quality and stability of the final solutions in optimization of vector Jiles-Atherton vector hysteresis model from a workbench containing a rotational single sheet tester.