Muestra métricas de impacto externas asociadas a la publicación. Para mayor detalle:
| Indexado |
|
||
| DOI | 10.1109/SPEC56436.2023.10408524 | ||
| Año | 2023 | ||
| Tipo |
Citas Totales
Autores Afiliación Chile
Instituciones Chile
% Participación
Internacional
Autores
Afiliación Extranjera
Instituciones
Extranjeras
Finite Control-Set Model Predictive Control (FCS- MPC) offers a simple concept of control for multilevel converters (MLIs), ease of implementation, and the ability to address multiple control objectives while including constraints. However, a high computational burden is required by FCS-MPC, which further increases with additional voltage levels. This paper proposes a two-stage hierarchical FCS-MPC control strategy based on line-to-line voltage-based prediction model, splitting the control into current control and capacitor voltage balance, using switching state redundancies. The aim is to reduce the number of voltage level iterations by means of pre-defined line-to-line voltage level tables, thus the computational burden with fast dynamic response too. Furthermore, the strategy avoids the use of weighting factors. The proposed control strategy is validated on a three-cell flying capacitor converter with 512 switching states, obtaining a reduction of about 91% in iteration cycles, maintaining the dynamic performance of standard FCS-MPC.
| Ord. | Autor | Género | Institución - País |
|---|---|---|---|
| 1 | Castillo, Cristian | - |
Universidad Arturo Prat - Chile
Universidad de Talca - Chile |
| 2 | Garcia, Cristian | - |
Universidad de Talca - Chile
|
| 3 | Acuna, Pablo | - |
Universidad de Talca - Chile
|
| Fuente |
|---|
| Fondo Nacional de Desarrollo Científico y Tecnológico |
| Universidad Arturo Prat |
| Universidad de Talca |
| AC3E |
| ANID-Human |
| Thematic Network RIBIERSE-CYTED |
| Agradecimiento |
|---|
| The authors would like to thank the financial support of FONDECYT Regular 1210208 Research Project, FONDECYT Regular 1231265 Research Project, Basal Project FB0008 (AC3E), and Thematic Network RIBIERSE-CYTED (723RT0150). Also, acknowledges the support of ANID-Human Capital Subdirection/National Doctorate/2021-21210830, Universidad Arturo Prat, and Universidad de Talca for the financial support provided. |