基于随机性与确定性混合优化算法的Jiles-Atherton磁滞模型参数提取

doi:10.19595/j.cnki.1000-6753.tces.180714

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Abstract The primary task of using J-A hysteresis model to simulate the hysteresis phenomenons of ferromagnetic materials is the model parameters' efficient identification. Owing to the slow convergence rate and low accuracy level of existing parameter extraction methods, a hybrid technique that couples simulated annealing (SA) with Levenberg-Marquardt (L-M) is proposed. This algorithm combines the merits of strong global search ability in SA and fast local convergence speed in L-M. In the initial iteration process, SA is used to quickly lock the optimized region. Then according to the introduced switching criterion, SA stops working, and its current solution is transferred to the L-M. Aiming at the problem of ill-conditioned matrix that appears in the process of parameter extraction when using traditional L-M, the sensitivity function matrix is normalized so as to obtain the normalized L-M, which is suitable for the rapid parameter identification of J-A model parameters. After receiving the solution provided by SA, the normalized L-M takes this values as its initial parameters for local search. The simulation and experimental results show that the proposed hybrid algorithm has the advantages of fast convergence and high accuracy at the same time.

Key words： J-A hysteresis model parameter extraction stochastic algorithm deterministic algorithm

Received: 26 April 2018 Published: 14 June 2019

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TM464

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	Liu Ren
	Li Lin
	Wang Yaqi
	Han Yu
	Liu Yang

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Liu Ren,Li Lin,Wang Yaqi等. Parameter Extraction for Jiles-Atherton Hysteresis Model Based on the Hybrid Technique of Stochastic and Deterministic Optimization Algorithm[J]. Transactions of China Electrotechnical Society, 2019, 34(11): 2260-2268.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.180714 OR https://dgjsxb.ces-transaction.com/EN/Y2019/V34/I11/2260

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