Performance Comparison of Model Predictive Control Methods for Active Front End Rectifiers
Active front-end rectifiers are tasked with generating high-quality, low-distortion sinusoidal line currents in the presence of adverse circuit conditions. When suitable control methods are applied to such rectifiers, significant performance improvements can be realized, especially under abnormal ut...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8533334/ |
| _version_ | 1818427579344879616 |
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| author | Eun-Su Jun Sangshin Kwak Taehyung Kim |
| author_facet | Eun-Su Jun Sangshin Kwak Taehyung Kim |
| author_sort | Eun-Su Jun |
| collection | DOAJ |
| description | Active front-end rectifiers are tasked with generating high-quality, low-distortion sinusoidal line currents in the presence of adverse circuit conditions. When suitable control methods are applied to such rectifiers, significant performance improvements can be realized, especially under abnormal utility conditions. Although several control methods based on model predictive control platforms have been recently developed, there is a lack of comparative studies of these methods in the literature. In this paper, the details and theoretical background of four model predictive control methods, namely, current control, virtual flux control, direct power control, and virtual flux direct power control, are presented. Then, the performance of these methods was compared by the way of experiments to determine the respective quality of the line current under various conditions, such as unbalanced input voltages, input voltage distortion, uncertainty in the parameters, and dc voltage fluctuation. In summary, based on the results of the experiments, the virtual flux control scheme was found to be distinctly superior to the other three schemes for distorted and unbalanced line voltages. |
| first_indexed | 2024-12-14T14:47:58Z |
| format | Article |
| id | doaj.art-27ea7f8715a14040a9906eb53e3ffe2c |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T14:47:58Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-27ea7f8715a14040a9906eb53e3ffe2c2022-12-21T22:57:14ZengIEEEIEEE Access2169-35362018-01-016772727728810.1109/ACCESS.2018.28811338533334Performance Comparison of Model Predictive Control Methods for Active Front End RectifiersEun-Su Jun0Sangshin Kwak1https://orcid.org/0000-0002-2890-906XTaehyung Kim2School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, South KoreaSchool of Electrical and Electronics Engineering, Chung-Ang University, Seoul, South KoreaDepartment of Electrical and Computer Engineering, University of Michigan–Dearborn, Dearborn, MI, USAActive front-end rectifiers are tasked with generating high-quality, low-distortion sinusoidal line currents in the presence of adverse circuit conditions. When suitable control methods are applied to such rectifiers, significant performance improvements can be realized, especially under abnormal utility conditions. Although several control methods based on model predictive control platforms have been recently developed, there is a lack of comparative studies of these methods in the literature. In this paper, the details and theoretical background of four model predictive control methods, namely, current control, virtual flux control, direct power control, and virtual flux direct power control, are presented. Then, the performance of these methods was compared by the way of experiments to determine the respective quality of the line current under various conditions, such as unbalanced input voltages, input voltage distortion, uncertainty in the parameters, and dc voltage fluctuation. In summary, based on the results of the experiments, the virtual flux control scheme was found to be distinctly superior to the other three schemes for distorted and unbalanced line voltages.https://ieeexplore.ieee.org/document/8533334/Active front end rectifiercurrent controldirect power controlmodel predictive controlvirtual flux control |
| spellingShingle | Eun-Su Jun Sangshin Kwak Taehyung Kim Performance Comparison of Model Predictive Control Methods for Active Front End Rectifiers IEEE Access Active front end rectifier current control direct power control model predictive control virtual flux control |
| title | Performance Comparison of Model Predictive Control Methods for Active Front End Rectifiers |
| title_full | Performance Comparison of Model Predictive Control Methods for Active Front End Rectifiers |
| title_fullStr | Performance Comparison of Model Predictive Control Methods for Active Front End Rectifiers |
| title_full_unstemmed | Performance Comparison of Model Predictive Control Methods for Active Front End Rectifiers |
| title_short | Performance Comparison of Model Predictive Control Methods for Active Front End Rectifiers |
| title_sort | performance comparison of model predictive control methods for active front end rectifiers |
| topic | Active front end rectifier current control direct power control model predictive control virtual flux control |
| url | https://ieeexplore.ieee.org/document/8533334/ |
| work_keys_str_mv | AT eunsujun performancecomparisonofmodelpredictivecontrolmethodsforactivefrontendrectifiers AT sangshinkwak performancecomparisonofmodelpredictivecontrolmethodsforactivefrontendrectifiers AT taehyungkim performancecomparisonofmodelpredictivecontrolmethodsforactivefrontendrectifiers |