Position Sensorless Control of Permanent Magnet Synchronous Motor Based on Improved Model Reference Adaptive Systems

To address the issues of poor stability and susceptibility to external disturbances in traditional model reference adaptive systems (MRASs) for permanent magnet synchronous motors (PMSMs), this paper proposes a sliding mode control strategy based on an improved model reference adaptive observer. First, the dynamic equations of the PMSM are used as the reference model, while the stator current equations incorporating speed variables are constructed as the adjustable model. Subsequently, a novel adaptive law is designed using Popov’s hyperstability theory to enhance the estimation accuracy of rotor position. A fractional-order system was introduced to construct both a fractional-order sliding surface and reaching law. Subsequently, a comparative study was conducted between the conventional integral terminal sliding surface and the proposed novel sliding mode reaching law. The results demonstrate that the new reaching law can adaptively adjust the switching gain based on system state variables. Under sudden load increases, the improved system achieves a 25% reduction in settling time compared to conventional sliding mode control (SMC), along with a 44% decrease in maximum speed fluctuation and a 42% reduction in maximum torque ripple, significantly enhancing dynamic response performance. Furthermore, a variable-gain terminal sliding mode controller is derived, and the stability of the closed-loop control system is rigorously proven using Lyapunov theory. Finally, simulations verify the effectiveness and feasibility of the proposed control strategy in improving system robustness and disturbance rejection capability.

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Publication Details

Journal
Energies
Published
2025-05-14
DOI
https://doi.org/10.3390/en18102531
Citations
4
Primary Topic
Sensorless Control of Electric Motors
Type
article
Field-Weighted Citation Impact
2.92

Funders

Controls
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article

Position Sensorless Control of Permanent Magnet Synchronous Motor Based on Improved Model Reference Adaptive Systems

Yiyong Wang, Tang Xiao, Meng Wang, Jian Liu et al.
4 citations
Energies
Sensorless Control of Electric Motors
2.92
article

Position Sensorless Control of Permanent Magnet Synchronous Motor Based on Improved Model Reference Adaptive Systems

Yiyong Wang, Tang Xiao, Meng Wang, Jian Liu, Lijun Jiang
article en
4 citations

Abstract

To address the issues of poor stability and susceptibility to external disturbances in traditional model reference adaptive systems (MRASs) for permanent magnet synchronous motors (PMSMs), this paper proposes a sliding mode control strategy based on an improved model reference adaptive observer. First, the dynamic equations of the PMSM are used as the reference model, while the stator current equations incorporating speed variables are constructed as the adjustable model. Subsequently, a novel adaptive law is designed using Popov’s hyperstability theory to enhance the estimation accuracy of rotor position. A fractional-order system was introduced to construct both a fractional-order sliding surface and reaching law. Subsequently, a comparative study was conducted between the conventional integral terminal sliding surface and the proposed novel sliding mode reaching law. The results demonstrate that the new reaching law can adaptively adjust the switching gain based on system state variables. Under sudden load increases, the improved system achieves a 25% reduction in settling time compared to conventional sliding mode control (SMC), along with a 44% decrease in maximum speed fluctuation and a 42% reduction in maximum torque ripple, significantly enhancing dynamic response performance. Furthermore, a variable-gain terminal sliding mode controller is derived, and the stability of the closed-loop control system is rigorously proven using Lyapunov theory. Finally, simulations verify the effectiveness and feasibility of the proposed control strategy in improving system robustness and disturbance rejection capability.

EnergiesVol. 18(10)
Shandong University of Technology (CN)
Natural Science Foundation of Shandong Province, Key Technology Research and Development Program of Shandong
Openalex Percentile: Top 9%
Sensorless Control of Electric Motors
2.92
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