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Mathematical Problems in Engineering
Volume 2015, Article ID 715018, 13 pages
Research Article

On the Generalization Capabilities of the Ten-Parameter Jiles-Atherton Model

Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy

Received 5 October 2015; Accepted 24 November 2015

Academic Editor: Xiao-Qiao He

Copyright © 2015 Gabriele Maria Lozito et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This work proposes an analysis on the generalization capabilities for the modified version of the classic Jiles-Atherton model for magnetic hysteresis. The modified model takes into account the use of dynamic parameterization, as opposed to the classic model where the parameters are constant. Two different dynamic parameterizations are taken into account: a dependence on the excitation and a dependence on the response. The identification process is performed by using a novel nonlinear optimization technique called Continuous Flock-of-Starling Optimization Cube (CFSO3), an algorithm belonging to the class of swarm intelligence. The algorithm exploits parallel architecture and uses a supervised strategy to alternate between exploration and exploitation capabilities. Comparisons between the obtained results are presented at the end of the paper.