Parameter Identification of Analytic Preisach Model Based on Improved Chimpanzee Algorithm
The analytical Preisach model solves the problems of large measurement error and numerical instability caused by discrete Everett function in the Preisach model,but there are many parameters and complicated identification problems in the model.In order to solve these problems,an improved chimp optimization algorithm based on multi-strategy fusion was proposed to achieve fast and accurate parameter identification of analytic Preisach model.Firstly,adaptive weighting factors were introduced to balance the global search and local exploitation capabilities.Secondly,the differential variance strategy was applied to update the position of individual populations,to enhance the exchange of information between individual algorithms and expand the search scope.Finally,a stochastic perturbation strategy using a combination of Cauchy and Gaussian variants was used to further enhance the algorithm's ability to jump out of local optima.Combined with the experimental data,genetic algorithm,chimpanzee algorithm and the algorithm proposed were used to identify the parameters of the analytical Preisach model.Based on the identification results,the hysteresis loops of the oriented silicon steel sheets were simulated.By comparing the results of hysteresis loop fitting degree,iteration times and fitness value,it can be seen that the proposed algorithm has the advantages of high identification accuracy and fast convergence speed in the identification of parameters of analytic Preisach model.