林国营,宋强,潘峰,肖厦颖,李开成,王凌云.基于改进人工鱼群算法的互感器Jiles-Atherton模型参数辨识[J].电测与仪表,2018,55(23):60-66. Ling Guoying,Song Qiang,Pan Feng,Xiao Xiaying,Li Kaicheng,Wang Lingyun.Parameter Identification of Jiles-Atherton Model Based on an Improved Artificial Fish Swarm Algorithm[J].Electrical Measurement & Instrumentation,2018,55(23):60-66.
基于改进人工鱼群算法的互感器Jiles-Atherton模型参数辨识
Parameter Identification of Jiles-Atherton Model Based on an Improved Artificial Fish Swarm Algorithm
Jiles-Atherton (J-A) model is widely used in the field of hysteresis modeling and simulation experiments of ferromagnetic materials. The accuracy of the five key parameters of the J-A model directly affects the fitting degree of the model. This paper proposes an improved algorithm, combining the artificial fish swarm algorithm (AFSA) and simulated annealing algorithm (SAA), which can identify the parameters of J-A model. In the proposed algorithm, the AFSA is employed to quickly locate the search domain in the vicinity of the global optimal result. When the fitting degree reaches a certain accuracy, the SAA is used to search the global optimal result precisely in a small range. Simulation results show that the proposed algorithm are able to solve the problem that the AFSA is not efficient enough and the SAA is hard to search in a wide range, and it can effectively improve the time-validity and the accuracy of J-A model parameter identification.
