A data driven model-free predictive current control for grid-connected inverters
Traditional model predictive current control has been widely studied in the field of grid-connected inverter control due to its rapid response and multi-objective optimization capabilities. A data driven model-free predictive current control strategy is proposed to address the problem of control per...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Electric Power Engineering Technology
2025-07-01
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| Series: | 电力工程技术 |
| Subjects: | |
| Online Access: | https://doi.org/10.12158/j.2096-3203.2025.04.021 |
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| author | Jindong YANG Xiran ZHANG Zeyu YANG Fei RONG |
| author_facet | Jindong YANG Xiran ZHANG Zeyu YANG Fei RONG |
| author_sort | Jindong YANG |
| collection | DOAJ |
| description | Traditional model predictive current control has been widely studied in the field of grid-connected inverter control due to its rapid response and multi-objective optimization capabilities. A data driven model-free predictive current control strategy is proposed to address the problem of control performance degradation caused by parameter mismatch in traditional model predictive current control. Firstly, the weighted average current method is used to reduce the order of the third-order LCL filter system, suppressing oscillations caused by LCL resonant frequency. Then, the ultra local model is adopted to simplify the traditional predictive current model, and a linear extended state observer is designed to estimate and compensate for system disturbances, thereby improving the accuracy of current prediction. Finally, the recursive least squares method is used to update the system model online based on system operating data, reducing the dependence of the control system on parameters. The simulation and hardware-in-the-loop experimental results demonstrate that compared to traditional model predictive current control, the proposed control strategy exhibits strong robustness and good steady-state performance under parameter mismatch conditions. |
| format | Article |
| id | doaj-art-1d8481edfcf044dbbfec919407490e1e |
| institution | Kabale University |
| issn | 2096-3203 |
| language | zho |
| publishDate | 2025-07-01 |
| publisher | Editorial Department of Electric Power Engineering Technology |
| record_format | Article |
| series | 电力工程技术 |
| spelling | doaj-art-1d8481edfcf044dbbfec919407490e1e2025-08-20T03:34:52ZzhoEditorial Department of Electric Power Engineering Technology电力工程技术2096-32032025-07-0144419720610.12158/j.2096-3203.2025.04.021240424374A data driven model-free predictive current control for grid-connected invertersJindong YANG0Xiran ZHANG1Zeyu YANG2Fei RONG3Electric Power Research Institute of Yunnan Power Grid Co., Ltd., Kunming 650217, ChinaElectric Power Research Institute of Yunnan Power Grid Co., Ltd., Kunming 650217, ChinaCollege of Electrical and Information Engineering, Hunan University, Changsha 410082, ChinaCollege of Electrical and Information Engineering, Hunan University, Changsha 410082, ChinaTraditional model predictive current control has been widely studied in the field of grid-connected inverter control due to its rapid response and multi-objective optimization capabilities. A data driven model-free predictive current control strategy is proposed to address the problem of control performance degradation caused by parameter mismatch in traditional model predictive current control. Firstly, the weighted average current method is used to reduce the order of the third-order LCL filter system, suppressing oscillations caused by LCL resonant frequency. Then, the ultra local model is adopted to simplify the traditional predictive current model, and a linear extended state observer is designed to estimate and compensate for system disturbances, thereby improving the accuracy of current prediction. Finally, the recursive least squares method is used to update the system model online based on system operating data, reducing the dependence of the control system on parameters. The simulation and hardware-in-the-loop experimental results demonstrate that compared to traditional model predictive current control, the proposed control strategy exhibits strong robustness and good steady-state performance under parameter mismatch conditions.https://doi.org/10.12158/j.2096-3203.2025.04.021finite set model predictive controlmodel-free controldata drivenultra local modelrecursive least squaresparameter mismatch |
| spellingShingle | Jindong YANG Xiran ZHANG Zeyu YANG Fei RONG A data driven model-free predictive current control for grid-connected inverters 电力工程技术 finite set model predictive control model-free control data driven ultra local model recursive least squares parameter mismatch |
| title | A data driven model-free predictive current control for grid-connected inverters |
| title_full | A data driven model-free predictive current control for grid-connected inverters |
| title_fullStr | A data driven model-free predictive current control for grid-connected inverters |
| title_full_unstemmed | A data driven model-free predictive current control for grid-connected inverters |
| title_short | A data driven model-free predictive current control for grid-connected inverters |
| title_sort | data driven model free predictive current control for grid connected inverters |
| topic | finite set model predictive control model-free control data driven ultra local model recursive least squares parameter mismatch |
| url | https://doi.org/10.12158/j.2096-3203.2025.04.021 |
| work_keys_str_mv | AT jindongyang adatadrivenmodelfreepredictivecurrentcontrolforgridconnectedinverters AT xiranzhang adatadrivenmodelfreepredictivecurrentcontrolforgridconnectedinverters AT zeyuyang adatadrivenmodelfreepredictivecurrentcontrolforgridconnectedinverters AT feirong adatadrivenmodelfreepredictivecurrentcontrolforgridconnectedinverters AT jindongyang datadrivenmodelfreepredictivecurrentcontrolforgridconnectedinverters AT xiranzhang datadrivenmodelfreepredictivecurrentcontrolforgridconnectedinverters AT zeyuyang datadrivenmodelfreepredictivecurrentcontrolforgridconnectedinverters AT feirong datadrivenmodelfreepredictivecurrentcontrolforgridconnectedinverters |