Identification of the parameters of the modified Lorentz function modelling hysteresis cycle

Issue title: Proceedings of the twelfth International Symposium on Interdisciplinary Electromagnetic, Mechanic and Biomedical Problems, ISEM Bad Gastein

Article type: Research Article

Authors: Nouicer, Abdelmadjid^{a; *} | Latreche, M.E.H.^a | Feliachi, M.^b | Méhasni, R.^a | Boubia, M.^a

Affiliations: [a] Département d'électrotechnique, Université Mentouri, route Ain elbey, Constantine, Algérie | [b] IREENA Laboratory, Saint Nazaire, France

Correspondence: [*] Corresponding author. Tel./Fax: +213 31 63 16 76; E-mail: [email protected]

Abstract: This paper presents the use of a hybrid algorithm based on the artificial neural networks (ANN) and the genetic algorithms (GA) for the identification of the parameters of the modified Lorentz function from the measured cycles. The principle of the identification is based on the minimization of a function criterion which represents the difference between the measured and simulated cycles.

Keywords: Genetic algorithms, hysteresis cycle, modified Lorentz function, neural network

DOI: 10.3233/JAE-2007-771

Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 25, no. 1-4, pp. 165-171, 2007