Speed Sensorless Control for IPMSMs Using a Modified MRAS with Gray Wolf Optimization Algorithm

Sun, X; Zhang, Y; Tian, X; Cao, J; Zhu, J

Speed Sensorless Control for IPMSMs Using a Modified MRAS with Gray Wolf Optimization Algorithm

Sun, X Zhang, Y Tian, X Cao, J Zhu, J

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Transportation Electrification, 2022, 8, (1), pp. 1326-1337
Issue Date:: 2022-03-01

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Field	Value	Language
dc.contributor.author	Sun, X
dc.contributor.author	Zhang, Y
dc.contributor.author	Tian, X
dc.contributor.author	Cao, J
dc.contributor.author	Zhu, J https://orcid.org/0000-0002-9763-4047
dc.date.accessioned	2023-03-21T00:36:52Z
dc.date.available	2023-03-21T00:36:52Z
dc.date.issued	2022-03-01
dc.identifier.citation	IEEE Transactions on Transportation Electrification, 2022, 8, (1), pp. 1326-1337
dc.identifier.issn	2332-7782
dc.identifier.issn	2332-7782
dc.identifier.uri	http://hdl.handle.net/10453/167854
dc.description.abstract	This article represents modified model reference adaptive system (MRAS) method for speed sensorless control of interior permanent magnet synchronous motor (IPMSM), which can estimate rotor speed and position information. To suppress the adverse effect of parameter variation on control performance, the stator resistance and the permanent magnet flux linkage are estimated and continuously updated in reference and adjustable model. Then, proportional-integral (PI) controller parameters of speed adaptive law obtained by MRAS are optimized by gray wolf optimization (GWO) algorithm. To get the smallest possible speed following error and reference current error, the objective function is designed with discretized rotor speed error and current error as variables. The simulation results show the better performance of rotor speed estimation is obtained with GWO algorithm.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Transactions on Transportation Electrification
dc.relation.isbasedon	10.1109/TTE.2021.3093580
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.title	Speed Sensorless Control for IPMSMs Using a Modified MRAS with Gray Wolf Optimization Algorithm
dc.type	Journal Article
utslib.citation.volume	8
utslib.for	0906 Electrical and Electronic 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	closed_access	*
dc.date.updated	2023-03-21T00:36:46Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	8
utslib.citation.issue	1

Abstract:

This article represents modified model reference adaptive system (MRAS) method for speed sensorless control of interior permanent magnet synchronous motor (IPMSM), which can estimate rotor speed and position information. To suppress the adverse effect of parameter variation on control performance, the stator resistance and the permanent magnet flux linkage are estimated and continuously updated in reference and adjustable model. Then, proportional-integral (PI) controller parameters of speed adaptive law obtained by MRAS are optimized by gray wolf optimization (GWO) algorithm. To get the smallest possible speed following error and reference current error, the objective function is designed with discretized rotor speed error and current error as variables. The simulation results show the better performance of rotor speed estimation is obtained with GWO algorithm.

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http://hdl.handle.net/10453/167854