We present an improved version of the Jiles-Atherton model for least square identification. We first use a simplified anhysteretic magnetization model to provide simple estimates of the initial parameters. Then we perform a normalization of sensitivity functions to improve the convergence of the Levenberg-Marquardt algorithm, leading to the emergence of optimal parameters. Experimental trials validate our method.
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Etien et al. (2008) studied this question.
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