A Composite Sliding Mode Control With the Modified Variable Exponential Reaching Law and Super-Twisting Extended State Observer for PMSM

In order to improve the dynamic performance and disturbance rejection of the permanent magnet synchronous motor (PMSM) speed regulation system, an improved non-singular fast terminal sliding mode speed controller based on a super-twisting extended state observer (STESO) is proposed. Firstly, in order to solve the contradiction between the system response speed and chattering, an improved nonsingular fast terminal sliding mode (INFTSM) speed controller based on a modified variable exponential reaching law (MVERL) is presented. The MVERL, which includes the variable gain term and power term of the system state variable, is proposed to self-adjust the speed of approaching the sliding surface according to the PMSM system state. This adaptive adjustment accelerates the convergence speed and weaken chattering. Secondly, to further improve the anti-disturbance performance of the PMSM control system, a super-twisting extended state observer (STESO) is designed to estimate the load disturbance and added to the output of the INFTSM for a feed-forward compensation item. The STESO can estimate and compensate for external disturbances in real-time to enhance the robustness and stability of the system. Finally, simulation and experimental results indicate that the STESO+INFTSM controller has better disturbances rejection capability, lower chattering and faster dynamic response.

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Publication Details

Journal
IEEE Sensors Journal
Published
2025-05-07
DOI
https://doi.org/10.1109/jsen.2025.3566028
Citations
4
Primary Topic
Iterative Learning Control Systems
Type
article
Field-Weighted Citation Impact
4.86

Funders

Controls
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article

A Composite Sliding Mode Control With the Modified Variable Exponential Reaching Law and Super-Twisting Extended State Observer for PMSM

T.S. Liu, Bo Xu, Shihong Ding, Wei Ji et al.
4 citations
IEEE Sensors Journal
Iterative Learning Control Systems
4.86
article

A Composite Sliding Mode Control With the Modified Variable Exponential Reaching Law and Super-Twisting Extended State Observer for PMSM

T.S. Liu, Bo Xu, Shihong Ding, Wei Ji, Xin Wang
article en
4 citations

Abstract

In order to improve the dynamic performance and disturbance rejection of the permanent magnet synchronous motor (PMSM) speed regulation system, an improved non-singular fast terminal sliding mode speed controller based on a super-twisting extended state observer (STESO) is proposed. Firstly, in order to solve the contradiction between the system response speed and chattering, an improved nonsingular fast terminal sliding mode (INFTSM) speed controller based on a modified variable exponential reaching law (MVERL) is presented. The MVERL, which includes the variable gain term and power term of the system state variable, is proposed to self-adjust the speed of approaching the sliding surface according to the PMSM system state. This adaptive adjustment accelerates the convergence speed and weaken chattering. Secondly, to further improve the anti-disturbance performance of the PMSM control system, a super-twisting extended state observer (STESO) is designed to estimate the load disturbance and added to the output of the INFTSM for a feed-forward compensation item. The STESO can estimate and compensate for external disturbances in real-time to enhance the robustness and stability of the system. Finally, simulation and experimental results indicate that the STESO+INFTSM controller has better disturbances rejection capability, lower chattering and faster dynamic response.

IEEE Sensors JournalVol. 25(12)
Jiangsu University (CN)
National Natural Science Foundation of China, Priority Academic Program Development of Jiangsu Higher Education Institutions
Peace, Justice and strong institutions
Openalex Percentile: Top 5%
Iterative Learning Control Systems
4.86
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A Composite Sliding Mode Control With the Modified Variable Exponential Reaching Law and Super-Twisting Extended State Observer for PMSM — T.S. Liu, Bo Xu, et al. · IEEE Sensors Journal (2025) | TGRS Research Map | TGRS