Model-Free Predictive Current Control of PMSM Based on Sliding Mode Disturbance Observer

Model predictive current control (MPCC) based on sliding mode disturbance observer (SMDO) effectively addresses the issues arising from parameter mismatches and unmodeled nonlinear elements in Permanent magnet synchronous motor (PMSM). However, conventional sliding mode faces a trade-off between reaching speed and chattering, and their closed-loop transfer functions are often challenging to derive. To overcome these limitations, this paper proposes a model-free predictive current control method based on an adaptive sliding mode disturbance observer (ASMDO-MFPCC). By exploiting a novel decoupled PMSM ultra-local model and a novel sliding mode control law, a discrete-time observer is designed to enhance convergence speed and suppress chattering. The stability of the observer is analyzed, and its parameter ranges are theoretically determined. Moreover, by linearizing the control law near the designed sliding surface, a complex vector linear model is established for the entire system, allowing closed-loop transfer function analysis to confirm that deadbeat performance can be preserved under accurate parameter settings. To further improve the system's robustness, a simple yet effective inductance identification algorithm is proposed for real-time calibration of the predictive control system. This algorithm operates independently of the observer design. Experimental results validate the effectiveness of the proposed current control scheme

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Publication Details

Journal
IEEE Transactions on Industry Applications
Published
2025-06-11
DOI
https://doi.org/10.1109/tia.2025.3578544
Citations
1
Primary Topic
Iterative Learning Control Systems
Type
article
Field-Weighted Citation Impact
1.21
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article

Model-Free Predictive Current Control of PMSM Based on Sliding Mode Disturbance Observer

Xiangyi Wang, Yiru Miao, Qiwei Xu, Yiming Wang et al.
1 citations
IEEE Transactions on Industry Applications
Iterative Learning Control Systems
1.21
article

Model-Free Predictive Current Control of PMSM Based on Sliding Mode Disturbance Observer

Xiangyi Wang, Yiru Miao, Qiwei Xu, Yiming Wang, Sheng Liu, Xue‐Feng Zhang
article en
1 citations

Abstract

Model predictive current control (MPCC) based on sliding mode disturbance observer (SMDO) effectively addresses the issues arising from parameter mismatches and unmodeled nonlinear elements in Permanent magnet synchronous motor (PMSM). However, conventional sliding mode faces a trade-off between reaching speed and chattering, and their closed-loop transfer functions are often challenging to derive. To overcome these limitations, this paper proposes a model-free predictive current control method based on an adaptive sliding mode disturbance observer (ASMDO-MFPCC). By exploiting a novel decoupled PMSM ultra-local model and a novel sliding mode control law, a discrete-time observer is designed to enhance convergence speed and suppress chattering. The stability of the observer is analyzed, and its parameter ranges are theoretically determined. Moreover, by linearizing the control law near the designed sliding surface, a complex vector linear model is established for the entire system, allowing closed-loop transfer function analysis to confirm that deadbeat performance can be preserved under accurate parameter settings. To further improve the system's robustness, a simple yet effective inductance identification algorithm is proposed for real-time calibration of the predictive control system. This algorithm operates independently of the observer design. Experimental results validate the effectiveness of the proposed current control scheme

IEEE Transactions on Industry ApplicationsVol. 61(6)
Chongqing University (CN)
Climate action
Openalex Percentile: Top 20%
Iterative Learning Control Systems
1.21
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Model-Free Predictive Current Control of PMSM Based on Sliding Mode Disturbance Observer — Xiangyi Wang, Yiru Miao, et al. · IEEE Transactions on Industry Applications (2025) | TGRS Research Map | TGRS