Research on Super-Twisting Sliding Mode Observer-Based Cascaded Speed Deadbeat Predictive Control for PMSLM

To improve the speed regulation performance of the permanent magnet synchronous linear motor (PMSLM), this paper proposes a cascaded deadbeat predictive control strategy based on a super-twisting sliding mode observer. Fisssrstly, a deadbeat current predictive control method is implemented in the current loop to enhance the accuracy of current prediction. Concurrently, a super-twisting sliding mode observer is integrated into the current loop to mitigate the impact of disturbances on current prediction accuracy. Subsequently, a deadbeat speed predictive control approach is applied in the speed loop to refine speed prediction accuracy. Additionally, a super-twisting sliding mode observer is incorporated into the speed loop to reduce the effects of external disturbances on speed prediction accuracy. Experimental results show that the proposed control strategy significantly improves the dynamic response and steady-state tracking precision of the system’s speed. Furthermore, it effectively enhances the system’s robustness against various disturbances.

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Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/icetac65964.2025.11144224
Primary Topic
Iterative Learning Control Systems
Type
article
Field-Weighted Citation Impact
0.00

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Controls
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article

Research on Super-Twisting Sliding Mode Observer-Based Cascaded Speed Deadbeat Predictive Control for PMSLM

W.T. Qian, Fei Dong, Zhou Yang, Jie Dong
Iterative Learning Control Systems
article

Research on Super-Twisting Sliding Mode Observer-Based Cascaded Speed Deadbeat Predictive Control for PMSLM

W.T. Qian, Fei Dong, Zhou Yang, Jie Dong
article en

Abstract

To improve the speed regulation performance of the permanent magnet synchronous linear motor (PMSLM), this paper proposes a cascaded deadbeat predictive control strategy based on a super-twisting sliding mode observer. Fisssrstly, a deadbeat current predictive control method is implemented in the current loop to enhance the accuracy of current prediction. Concurrently, a super-twisting sliding mode observer is integrated into the current loop to mitigate the impact of disturbances on current prediction accuracy. Subsequently, a deadbeat speed predictive control approach is applied in the speed loop to refine speed prediction accuracy. Additionally, a super-twisting sliding mode observer is incorporated into the speed loop to reduce the effects of external disturbances on speed prediction accuracy. Experimental results show that the proposed control strategy significantly improves the dynamic response and steady-state tracking precision of the system’s speed. Furthermore, it effectively enhances the system’s robustness against various disturbances.

Anhui University (CN), Anhui and Huaihe River Institute of Hydraulic Research (CN)
Natural Science Foundation of Anhui Province
Openalex Percentile: Top 71%
Iterative Learning Control Systems
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