The accuracy of the magnetic core model is important to the analysis and design of the flux-gate sensor. The Jiles-Atherton model (J-A model) is the mostly used model to describe the hysteresis characteristics of the flux-gate core. But the parameters of J-A model are difficult to identify. In this paper, Fruit Fly Optimization Algorithm (FOA) is proposed to identify the parameters of the J-A model. In order to enhance the performance of the identification, a Modified Fruit Fly Optimization Algorithm (MFOA) is applied to extract the parameters of the flux-gate core. The effectiveness of MFOA is verified through five typical test functions. The influence of variation factor on the performance of MFOA is discussed. The impact of variation factor on parameters extraction of hysteresis loop is studied. It is shown that MFOA with appropriate selection of variation factor will get better performance in the accuracy, stability, and simulation time compared to those of PSO and FOA.
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