基于改进黑猩猩算法的解析Preisach模型参数辨识
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TM271

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河南省高等学校重点科研项目计划(22A470014);河南省科技攻关项目(232102211050);郑州轻工业大学青年骨干教师项目(13502010006)


Parameter identification of analytic Preisach model based on improved Chimpanzee algorithm
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    摘要:

    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,本文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。该算法首先应用改进的logistic映射和动态反向学习策略进行种群初始化;其次提出一种新的动态非线性递减收敛因子平衡全局搜索和局部开发能力;再次将差分变异引入到种群个体位置更新中,增加种群多样性、扩大搜索范围;最后使用随机变异策略对全局最优位置进行扰动更新,跳出局部最优。结合实验数据,分别使用遗传算法、黑猩猩算法与本文所提算法对解析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、迭代次数与适应度值等三方面的结果对比可得,本文所提算法在解析Preisach 模型的参数辨识上兼具辨识精度高、收敛速度快的优点。
    关键词:解析Preisach模型;Everett函数;参数辨识;改进黑猩猩优化算法;磁滞回线

    Abstract:

    The analytical Preisach model solves the problems of large measurement error and numerical instability caused by discrete Everett function in the Preisach model, but the analytical Preisach model also has many parameters and complex identification problems. To solve these problems, this paper proposes an improved chimp optimization algorithm integrating multiple strategies to achieve fast and accurate parameter identification of analytic Preisach model. Firstly, the improved logistic mapping and dynamic reverse learning strategy were used to initialize the population. Secondly, a new dynamic nonlinear decreasing convergence factor is proposed to balance global search and local exploitation capabilities. Thirdly, differential variation was introduced into individual location updating to increase population diversity and expand search scope. Finally, stochastic variation strategy is used to update the global optimal position and jump out of the local optimal position. Combined with the experimental data, genetic algorithm, chimpanzee algorithm and the algorithm proposed in this paper were respectively used to identify the parameters of the analytic Preisach model. By comparing the results of fit degree, iteration number and fitness value of hysteresis loop, 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.

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李丹丹,介百坤,朱石磊,等. 基于改进黑猩猩算法的解析Preisach模型参数辨识[J]. 科学技术与工程, 2024, 24(17): 7140-7147.
Li Dandan, Jie Baikun, Zhu Shilei, et al. Parameter identification of analytic Preisach model based on improved Chimpanzee algorithm[J]. Science Technology and Engineering,2024,24(17):7140-7147.

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  • 收稿日期:2023-06-28
  • 最后修改日期:2024-04-11
  • 录用日期:2023-11-02
  • 在线发布日期: 2024-06-24
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