Modified FOA Applied to Parameter Extraction of Flux-Gate Core

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 h on the performance of mfoa is discussed. the impact of variation factor h on parameters extraction of hysteresis loop is studied. it is shown that mfoa with appropriate selection of variation factor h will get better performance in the accuracy,stability,and simulation time compared to those of pso and foa. © 2017 wenjuan jiang et al.