Softcomputing for the identification of the Jiles-Atherton model parameters

This paper presents a Jiles-Atherton hysteresis model identification method based on a partnership of heuristic techniques and fuzzy logic (softcomputing). Two different softcomputing approaches are proposed and analyzed: a partnership between genetic algorithms (GAs) and fuzzy logic (FL) and one between GAs and simulated annealing (SA). Validations of both symmetric (saturated or minor loops) and asymmetric loops are described.

[1]  C. Ragusa,et al.  Predicting loss in magnetic steels under arbitrary induction waveform and with minor hysteresis loops , 2004, IEEE Transactions on Magnetics.

[2]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[3]  Alessandro Salvini,et al.  A neuro-genetic and time-frequency approach to macromodeling dynamic hysteresis in the harmonic regime , 2003 .

[4]  F. Preisach.  Über die magnetische Nachwirkung , 1935 .

[5]  Peter R. Wilson,et al.  Definition and application of magnetic material metrics in modeling and optimization , 2001 .

[6]  K. H. Carpenter.  Simple models for dynamic hysteresis which add frequency-dependent losses to static models , 1998 .

[7]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[8]  David Jiles,et al.  A self consistent generalized model for the calculation of minor loop excursions in the theory of hysteresis , 1992, 1992. Digests of Intermag. International Magnetics Conference.

[9]  D. Jiles,et al.  Theory of ferromagnetic hysteresis , 1986 .

[10]  Alessandro Salvini,et al.  Genetic algorithms and neural networks generalizing the Jiles-Atherton model of static hysteresis for dynamic loops , 2002 .

[11]  N. Sadowski,et al.  Real coded genetic algorithm for Jiles-Atherton model parameters identification , 2004, IEEE Transactions on Magnetics.

[12]  Lotfi A. Zadeh,et al.  Soft computing and fuzzy logic , 1994, IEEE Software.

[13]  Alessandro Salvini,et al.  Generalization of the static Preisach model for dynamic hysteresis by a genetic approach , 2003 .

[14]  S. Prigozy.  PSPICE computer modeling of hysteresis effects , 1993 .

[15]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[16]  Albert Y. Zomaya,et al.  Genetic Scheduling for Parallel Processor Systems: Comparative Studies and Performance Issues , 1999, IEEE Trans. Parallel Distributed Syst..

[17]  Andrew D. Brown,et al.  Optimizing the Jiles-Atherton model of hysteresis by a genetic algorithm , 2001 .

[18]  Andrew D. Brown,et al.  Magnetic material model characterization and optimization software , 2002 .