Sliding Mode Direct Torque Control of SPMSMs Based on a Hybrid Wolf Optimization Algorithm

Jin, Z; Sun, X; Lei, G; Guo, Y; Zhu, J

Sliding Mode Direct Torque Control of SPMSMs Based on a Hybrid Wolf Optimization Algorithm

Jin, Z Sun, X Lei, G

Guo, Y

Zhu, J

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Transactions on Industrial Electronics, 2022, 69, (5), pp. 4534-4544
Issue Date:: 2022-05-01

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Field	Value	Language
dc.contributor.author	Jin, Z
dc.contributor.author	Sun, X
dc.contributor.author	Lei, G https://orcid.org/0000-0002-8369-6802
dc.contributor.author	Guo, Y https://orcid.org/0000-0001-6182-0684
dc.contributor.author	Zhu, J
dc.date.accessioned	2022-05-07T09:09:28Z
dc.date.available	2022-05-07T09:09:28Z
dc.date.issued	2022-05-01
dc.identifier.citation	IEEE Transactions on Industrial Electronics, 2022, 69, (5), pp. 4534-4544
dc.identifier.issn	0278-0046
dc.identifier.issn	1557-9948
dc.identifier.uri	http://hdl.handle.net/10453/157105
dc.description.abstract	Direct torque control has been widely used to control surface-mounted permanent magnet synchronous motors (SPMSMs). To reduce the torque ripple and improve the flux tracking accuracy of SPMSM drives, sliding mode direct torque control (SMDTC) was developed. However, its optimal performance is hardly obtained by trial and error tuning of the control parameters. Hence, a hybrid wolf optimization algorithm (HWOA) is proposed to automatically adjust the controller's parameters of SMDTC for SPMSMs in this article. This algorithm combines the grey wolf optimization algorithm and coyote optimization algorithm. A conversion probability is designed to use them simultaneously. The proposed HWOA holds the advantages of the two algorithms. It converges very fast and can avoid local optimums effectively. Furthermore, a special fitness index with penalty terms is designed to enhance flux tracking accuracy and reduce the torque ripple of SPMSM drives. The superiority of the proposed control method is verified by an experiment.
dc.language	English
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation.ispartof	IEEE Transactions on Industrial Electronics
dc.relation.isbasedon	10.1109/TIE.2021.3080220
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering
dc.subject.classification	Electrical & Electronic Engineering
dc.title	Sliding Mode Direct Torque Control of SPMSMs Based on a Hybrid Wolf Optimization Algorithm
dc.type	Journal Article
utslib.citation.volume	69
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
utslib.copyright.embargo	2024-05-31T00:00:00+1000Z
dc.date.updated	2022-05-07T09:08:49Z
pubs.issue	5
pubs.publication-status	Published
pubs.volume	69
utslib.citation.issue	5

Abstract:

Direct torque control has been widely used to control surface-mounted permanent magnet synchronous motors (SPMSMs). To reduce the torque ripple and improve the flux tracking accuracy of SPMSM drives, sliding mode direct torque control (SMDTC) was developed. However, its optimal performance is hardly obtained by trial and error tuning of the control parameters. Hence, a hybrid wolf optimization algorithm (HWOA) is proposed to automatically adjust the controller's parameters of SMDTC for SPMSMs in this article. This algorithm combines the grey wolf optimization algorithm and coyote optimization algorithm. A conversion probability is designed to use them simultaneously. The proposed HWOA holds the advantages of the two algorithms. It converges very fast and can avoid local optimums effectively. Furthermore, a special fitness index with penalty terms is designed to enhance flux tracking accuracy and reduce the torque ripple of SPMSM drives. The superiority of the proposed control method is verified by an experiment.

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http://hdl.handle.net/10453/157105