Abstract
This paper proposes a data-model-based model-free predictive control (DM-MFPC) for LCL-filtered power converters, which effectively enhances the parameter robustness of grid-side current control under mismatched parameters. The proposed DM-MFPC not only establishes the data-model of LCL-filtered power converter, but also achieves the real-time updating of data-model for accurate model-free prediction calculation. The hardware experimental platform also is built for evaluating the grid-side current performance under accurate parameters and mismatched parameters compared with conventional model predictive control.
| Original language | English |
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| Title of host publication | 2025 IEEE 8th International Electrical and Energy Conference (CIEEC) |
| Place of Publication | Piscataway, NJ |
| Pages | 2017-2022 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798331542979, 9798331542962 |
| DOIs | |
| Publication status | Published - 15 Aug 2025 |
| Event | 8th IEEE International Electrical and Energy Conference, CIEEC 2025 - Changsha, China Duration: 16 May 2025 → 18 May 2025 |
Publication series
| Name | China International Electrical and Energy Conference (CIEEC) |
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Conference
| Conference | 8th IEEE International Electrical and Energy Conference, CIEEC 2025 |
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| Country/Territory | China |
| City | Changsha |
| Period | 16/05/25 → 18/05/25 |
Funding
This work was supported by the National Key Research and Development Program of China under Grant 2022YFE0196300, and supported by the Science, Technology & Innovation Funding Authority (STDF) under Grant number 46505. J. Rodriguez acknowledges the support of ANID through project AFB240002.
Keywords
- data-model
- LCL filter
- model-free predictive control
- power converter
