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| DOI | 10.1109/IFEEC58486.2023.10458639 | ||
| Año | 2023 | ||
| Tipo |
Citas Totales
Autores Afiliación Chile
Instituciones Chile
% Participación
Internacional
Autores
Afiliación Extranjera
Instituciones
Extranjeras
Three-phase interleaved boost converter has the characteristics of small input current ripple and high power density. However, unknown external disturbances, temperature change can cause inductive device parameter mismatch and control performance degradation. To solve this problem, this paper proposes a model predictive control method based on compensation function observer (CFO). Firstly, the mathematical model of the boost converter is established, and a predictive model including parameter disturbance terms is constructed. Secondly, the CFO is designed to observe the disturbance terms in the system and compensate for the fixed errors of the traditional observer, thereby improving the accuracy of the system. Thirdly, to achieve better dynamic performance, both the inner and outer loops employ model predictive control (MPC). Finally, the effectiveness and superiority of the proposed method were validated through experimental tests on the dynamic performance and robustness of the boost converter.
| Ord. | Autor | Género | Institución - País |
|---|---|---|---|
| 1 | Yu, Xinhong | - |
Chinese Academy of Sciences - China
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| 2 | Jiang, Tiantian | - |
Fuzhou University - China
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| 3 | Xu, Libin | - |
Fuzhou University - China
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| 4 | Wei, Yao | - |
Chinese Academy of Sciences - China
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| 5 | Wang, Fengxiang | - |
Chinese Academy of Sciences - China
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| 6 | RODRIGUEZ-PEREZ, JOSE RAMON | Hombre |
Universidad San Sebastián - Chile
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| Fuente |
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| National Natural Science Foundation of China |
| China Postdoctoral Science Foundation |
| Science and Technology Program of Hunan Province |
| Agencia Nacional de Investigación y Desarrollo |
| Agradecimiento |
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| This work was supported in part by the National Natural Science Funds of China under Grant 52277070, China Postdoctoral Science Foundation 2023M730598, in part by the Science and Technology Program of Fujian Province 2021I0039, 2021T3064, 2021T3035, 2022T3070, and J. Rodriguez acknowledges the support of ANID through projects FB0008, 1210208 and 1221293. |