Multiple-Voltage-Vector Model-Free Predictive Deadbeat Control With Updated Reference Voltage Vector for PMSM Drive

Model predictive control (MPC) has been extensively investigated for its impressive dynamic response and efficacy in controlling non-linear systems. However, MPC faces challenges in terms of robustness, primarily due to its dependency on system parameters. In contrast, model-free predictive control (MFPC) offers an alternative that relies on the inputs and outputs of the system without applying system parameters in each control period. To avoid the problem of the stator current gradient update stagnation existing in the conventional MFPC strategy, this article proposes an enhanced MFPC strategy based on a novel reference voltage vector (VV) updating mechanism. In the proposed strategy, the reference VVs for the present control period are determined by evaluating the difference between the reference current and the sampling current, which is related to the previously calculated VVs of the contiguous control period. By substituting the current gradient with the updated reference VVs, the proposed strategy effectively reduces the interferences arising from inaccurate current gradients, enhancing the steady-state performance of the system. The proposed MFPC is verified using a laboratory 0.5 kw permanent magnet synchronous motor drive setup.

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Publication Details

Journal
IEEE Transactions on Power Electronics
Published
2024-08-19
DOI
https://doi.org/10.1109/tpel.2024.3445497
Citations
10
Primary Topic
Multilevel Inverters and Converters
Type
article
Field-Weighted Citation Impact
2.09
Controls
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article

Multiple-Voltage-Vector Model-Free Predictive Deadbeat Control With Updated Reference Voltage Vector for PMSM Drive

Jiefeng Hu, Yang Xiao, Huiqing Wen, Kai Ni et al.
10 citations
IEEE Transactions on Power Electronics
Multilevel Inverters and Converters
2.09
article

Multiple-Voltage-Vector Model-Free Predictive Deadbeat Control With Updated Reference Voltage Vector for PMSM Drive

Jiefeng Hu, Yang Xiao, Huiqing Wen, Kai Ni, José Rodríguez, Mingdi Fan, Xiangcheng Li, Jun Sun, Hui Yang, Yong Yang
article en
10 citations

Abstract

Model predictive control (MPC) has been extensively investigated for its impressive dynamic response and efficacy in controlling non-linear systems. However, MPC faces challenges in terms of robustness, primarily due to its dependency on system parameters. In contrast, model-free predictive control (MFPC) offers an alternative that relies on the inputs and outputs of the system without applying system parameters in each control period. To avoid the problem of the stator current gradient update stagnation existing in the conventional MFPC strategy, this article proposes an enhanced MFPC strategy based on a novel reference voltage vector (VV) updating mechanism. In the proposed strategy, the reference VVs for the present control period are determined by evaluating the difference between the reference current and the sampling current, which is related to the previously calculated VVs of the contiguous control period. By substituting the current gradient with the updated reference VVs, the proposed strategy effectively reduces the interferences arising from inaccurate current gradients, enhancing the steady-state performance of the system. The proposed MFPC is verified using a laboratory 0.5 kw permanent magnet synchronous motor drive setup.

IEEE Transactions on Power ElectronicsVol. 40(5)
Federation University (AU), San Sebastián University (CL), Soochow University (CN), Xi’an Jiaotong-Liverpool University (CN), Southeast University (CN)
Affordable and clean energy
Openalex Percentile: Top 13%
Multilevel Inverters and Converters
2.09
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