Parameter Identification of Jiles-Atherton Model Based on Levy Whale Optimization Algorithm
The Jiles-Atherton model is key to researching the hysteresis loop. The focus of scholars across various countries has always been the parameter identification of the Jiles-Atherton model. This paper on the Levy whale optimization algorithm (LWOA), based on the whale optimization algorithm (WOA), pr...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9802987/ |
| _version_ | 1828827987996311552 |
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| author | Zhigang Chen Yue Yu Yanxue Wang |
| author_facet | Zhigang Chen Yue Yu Yanxue Wang |
| author_sort | Zhigang Chen |
| collection | DOAJ |
| description | The Jiles-Atherton model is key to researching the hysteresis loop. The focus of scholars across various countries has always been the parameter identification of the Jiles-Atherton model. This paper on the Levy whale optimization algorithm (LWOA), based on the whale optimization algorithm (WOA), proposes to overcome the disadvantage that WOA tends to involve the local optimum. The recommended algorithm uses the Levy flight strategy instead of the encircling prey policy since the former improves the global search. Therefore, the new algorithm is better at stability and calculation accuracy. To substantiate the efficacy of the proposed algorithm, it is tested against six benchmark functions and compared with the WOA, particle swarm optimization (PSO), grey wolf algorithm (GWO), and shuffled frog leaping algorithm (SFLA). In addition, the proposed algorithm is applied to realize two classical engineering problems, such as the tension/compression spring and welded beam design issues. The experimental findings reveal that the proposed algorithm is highly competitive with metaheuristic optimizers and improves the algorithm’s performance. To address the poor stability of the J-A model parameter identification, an improved calculation method for parameter <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> and the reduced parameter ranges of the model parameters <inline-formula> <tex-math notation="LaTeX">${a}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> were combined with LWOA. The proposed algorithm is called C-LWOA, which is compared with LWOA, PSO, GWO, SFLA, and the cuckoo search (CS) based on the data reported in the literature. Moreover, the simulation results demonstrate that the stability and calculation accuracy of the parameter identification by the C-LWOA was significantly strengthened. Equally important, the calculation error was within 0.2%. Finally, the proposed algorithm was subsequently used to fit the actual measurements of the hysteresis loop of permalloy. |
| first_indexed | 2024-12-12T15:11:29Z |
| format | Article |
| id | doaj.art-6cec44623dca42ec8ffa6fb67f8976ac |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-12T15:11:29Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-6cec44623dca42ec8ffa6fb67f8976ac2022-12-22T00:20:36ZengIEEEIEEE Access2169-35362022-01-0110667116672110.1109/ACCESS.2022.31854149802987Parameter Identification of Jiles-Atherton Model Based on Levy Whale Optimization AlgorithmZhigang Chen0https://orcid.org/0000-0002-4698-0804Yue Yu1Yanxue Wang2Department of Mechanical and Electrical and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, ChinaDepartment of Mechanical and Electrical and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, ChinaDepartment of Mechanical and Electrical and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing, ChinaThe Jiles-Atherton model is key to researching the hysteresis loop. The focus of scholars across various countries has always been the parameter identification of the Jiles-Atherton model. This paper on the Levy whale optimization algorithm (LWOA), based on the whale optimization algorithm (WOA), proposes to overcome the disadvantage that WOA tends to involve the local optimum. The recommended algorithm uses the Levy flight strategy instead of the encircling prey policy since the former improves the global search. Therefore, the new algorithm is better at stability and calculation accuracy. To substantiate the efficacy of the proposed algorithm, it is tested against six benchmark functions and compared with the WOA, particle swarm optimization (PSO), grey wolf algorithm (GWO), and shuffled frog leaping algorithm (SFLA). In addition, the proposed algorithm is applied to realize two classical engineering problems, such as the tension/compression spring and welded beam design issues. The experimental findings reveal that the proposed algorithm is highly competitive with metaheuristic optimizers and improves the algorithm’s performance. To address the poor stability of the J-A model parameter identification, an improved calculation method for parameter <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> and the reduced parameter ranges of the model parameters <inline-formula> <tex-math notation="LaTeX">${a}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> were combined with LWOA. The proposed algorithm is called C-LWOA, which is compared with LWOA, PSO, GWO, SFLA, and the cuckoo search (CS) based on the data reported in the literature. Moreover, the simulation results demonstrate that the stability and calculation accuracy of the parameter identification by the C-LWOA was significantly strengthened. Equally important, the calculation error was within 0.2%. Finally, the proposed algorithm was subsequently used to fit the actual measurements of the hysteresis loop of permalloy.https://ieeexplore.ieee.org/document/9802987/Jiles-Atherton modelhysteresis looplevy flightwhale optimization algorithm |
| spellingShingle | Zhigang Chen Yue Yu Yanxue Wang Parameter Identification of Jiles-Atherton Model Based on Levy Whale Optimization Algorithm IEEE Access Jiles-Atherton model hysteresis loop levy flight whale optimization algorithm |
| title | Parameter Identification of Jiles-Atherton Model Based on Levy Whale Optimization Algorithm |
| title_full | Parameter Identification of Jiles-Atherton Model Based on Levy Whale Optimization Algorithm |
| title_fullStr | Parameter Identification of Jiles-Atherton Model Based on Levy Whale Optimization Algorithm |
| title_full_unstemmed | Parameter Identification of Jiles-Atherton Model Based on Levy Whale Optimization Algorithm |
| title_short | Parameter Identification of Jiles-Atherton Model Based on Levy Whale Optimization Algorithm |
| title_sort | parameter identification of jiles atherton model based on levy whale optimization algorithm |
| topic | Jiles-Atherton model hysteresis loop levy flight whale optimization algorithm |
| url | https://ieeexplore.ieee.org/document/9802987/ |
| work_keys_str_mv | AT zhigangchen parameteridentificationofjilesathertonmodelbasedonlevywhaleoptimizationalgorithm AT yueyu parameteridentificationofjilesathertonmodelbasedonlevywhaleoptimizationalgorithm AT yanxuewang parameteridentificationofjilesathertonmodelbasedonlevywhaleoptimizationalgorithm |