基于改进黑猩猩算法的解析Preisach模型参数辨识

Parameter Identification of Analytic Preisach Model Based on Improved Chimpanzee Algorithm

解析Preisach模型解决了Preisach模型因离散Everett函数造成的测量误差大、数值不稳定的问题,但是解析Preisach模型同时存在参数多、辨识复杂的问题。针对上述问题,提出一种融合多策略的改进黑猩猩优化算法,来实现对解析Preisach模型的参数快速、精确辨识。首先,引入自适应权重因子来平衡全局搜索和局部开发能力;其次,将差分变异策略应用到种群个体位置更新中,增强算法个体间的信息交流,扩大搜索范围;最后,使用柯西变异和高斯变异相结合的随机扰动策略,进一步增强算法跳出局部最优的能力。结合实验数据,分别使用遗传算法、黑猩猩算法、正弦余弦黑猩猩算法与所提算法对解析Preisach模型参数进行辨识,并基于辨识结果对取向硅钢片的磁滞回线进行模拟。通过磁滞回线拟合度、适应度值变化以及损耗误差分析3个方面的结果对比可得,所提算法在解析Preisach模型的参数辨识上兼具辨识精度高、收敛速度快的优点。

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.