Research on Sensorless and Robust Control of High-Speed Surface-Mounted Permanent Magnet Synchronous Motors

Xu, Kai

Research on Sensorless and Robust Control of High-Speed Surface-Mounted Permanent Magnet Synchronous Motors

Xu, Kai

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Publication Type:: Thesis
Issue Date:: 2026

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Field	Value	Language
dc.contributor.author	Xu, Kai
dc.date.accessioned	2026-07-26T23:58:57Z
dc.date.available	2026-07-26T23:58:57Z
dc.date.issued	2026
dc.identifier.uri	http://hdl.handle.net/10453/195801
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	High-speed permanent magnet synchronous motors (PMSMs) are increasingly adopted in electric vehicles, high-speed rail traction, aerospace, and flywheel energy storage systems. The advantages of PMSMs include high efficiency, compact design, and excellent dynamic performance. However, their application is limited by three key challenges: ensuring reliable and efficient performance analysis, achieving accurate sensorless control at high speeds and in flux-weakening (FW) regions, and maintaining robustness under disturbances and parameter variations. This thesis addresses these challenges through advanced modeling, estimation, and adaptive robust control strategies. First, to strengthen fundamental analysis, a proper orthogonal decomposition-based model order reduction (MOR) method is developed for bearingless PMSMs. The approach drastically reduces computation time while preserving high accuracy in flux density, torque, levitation force, and dynamic response compared with finite element analysis. These achieve relative errors below 3.5%, enabling efficient and precise loss prediction across wide operating ranges. Second, for sensorless control, a cascade high-order extended state observer (CHESO) is introduced to accurately estimate back-electromotive force, rotor position, load torque, and disturbances. Unlike conventional linear ESOs (LESOs) limited by bandwidth and phase lag, CHESO provides improved accuracy and robustness at high speeds. To further enhance performance in the FW operation, a second-order generalized integrator (SOGI) combined with a high-order ESO (HESO) framework is proposed. The SOGI suppresses noise and harmonics, while the HESO reduces phase lag and expands bandwidth. Experimental results show that these approaches reduce rotor position errors and significantly improve harmonic suppression. Finally, to address robust control, adaptive feedforward torque compensation and an adaptive linear active disturbance rejection controller (ALADRC) are developed. The feedforward strategy enhances dynamic response and disturbance rejection, while ALADRC adjusts bandwidth in real time to cope with FW conditions. The results confirm reductions in speed error amplitudes, improved stability under parameter mismatches, and stronger robustness compared with conventional PI and LESO-based methods. In conclusion, this thesis advances both analysis and control of high-speed PMSMs. The proposed MOR provides an efficient tool for design and evaluation, while CHESO, SOGI-HESO, and ALADRC deliver accurate and robust sensorless control across wide speed ranges. Together, these contributions enable reliable and high-performance operation of high-speed PMSMs in critical energy and transportation applications, supporting the transition to sustainable and intelligent electrification.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/195801/1/thesis.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	© 2026 Kai Xu
dc.rights	au.edu.uts.lib/cph
dc.title	Research on Sensorless and Robust Control of High-Speed Surface-Mounted Permanent Magnet Synchronous Motors	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

High-speed permanent magnet synchronous motors (PMSMs) are increasingly adopted in electric vehicles, high-speed rail traction, aerospace, and flywheel energy storage systems. The advantages of PMSMs include high efficiency, compact design, and excellent dynamic performance. However, their application is limited by three key challenges: ensuring reliable and efficient performance analysis, achieving accurate sensorless control at high speeds and in flux-weakening (FW) regions, and maintaining robustness under disturbances and parameter variations. This thesis addresses these challenges through advanced modeling, estimation, and adaptive robust control strategies. First, to strengthen fundamental analysis, a proper orthogonal decomposition-based model order reduction (MOR) method is developed for bearingless PMSMs. The approach drastically reduces computation time while preserving high accuracy in flux density, torque, levitation force, and dynamic response compared with finite element analysis. These achieve relative errors below 3.5%, enabling efficient and precise loss prediction across wide operating ranges. Second, for sensorless control, a cascade high-order extended state observer (CHESO) is introduced to accurately estimate back-electromotive force, rotor position, load torque, and disturbances. Unlike conventional linear ESOs (LESOs) limited by bandwidth and phase lag, CHESO provides improved accuracy and robustness at high speeds. To further enhance performance in the FW operation, a second-order generalized integrator (SOGI) combined with a high-order ESO (HESO) framework is proposed. The SOGI suppresses noise and harmonics, while the HESO reduces phase lag and expands bandwidth. Experimental results show that these approaches reduce rotor position errors and significantly improve harmonic suppression. Finally, to address robust control, adaptive feedforward torque compensation and an adaptive linear active disturbance rejection controller (ALADRC) are developed. The feedforward strategy enhances dynamic response and disturbance rejection, while ALADRC adjusts bandwidth in real time to cope with FW conditions. The results confirm reductions in speed error amplitudes, improved stability under parameter mismatches, and stronger robustness compared with conventional PI and LESO-based methods. In conclusion, this thesis advances both analysis and control of high-speed PMSMs. The proposed MOR provides an efficient tool for design and evaluation, while CHESO, SOGI-HESO, and ALADRC deliver accurate and robust sensorless control across wide speed ranges. Together, these contributions enable reliable and high-performance operation of high-speed PMSMs in critical energy and transportation applications, supporting the transition to sustainable and intelligent electrification.

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