Computational Analysis of the Long Horizon FCS-MPC Problem for Power Converters

Abstract—Long prediction horizon finite control set model predictive control (LPH-FCS-MPC) for power converters can be reformulated as a box-constrained integer-least squares (ILS) problem to find the optimal control action without requiring an exhaustive search. Instead, the solution can be found b...

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Detalles Bibliográficos
Autores: Zafra, Eduardo, Vázquez Pérez, Sergio, Geyer, Tobías, Aguilera, Ricardo P., Freire Macías, Emilio, García Franquelo, Leopoldo
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2024
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/176539
Acceso en línea:https://hdl.handle.net/11441/176539
https://doi.org/10.1109/TPEL.2024.3419060
Access Level:acceso abierto
Palabra clave:Digital control
predictive control
three -phase dc-ac inverters
Descripción
Sumario:Abstract—Long prediction horizon finite control set model predictive control (LPH-FCS-MPC) for power converters can be reformulated as a box-constrained integer-least squares (ILS) problem to find the optimal control action without requiring an exhaustive search. Instead, the solution can be found by means of a sphere decoding method that still presents several intricacies regarding its complexity and its variable computational cost. This paper provides a study of the computational behavior of this ap- proach. Special emphasis is placed on how the generator matrix is calculated, either as a lower or an upper triangular structure. This choice decides whether the switching sequences are explored forward- or backward-in-time during the optimization process. In this work, it is explained how this selection holds a great impact on the computational burden of the algorithm. Similarly, it is also analyzed how the tuning of the FCS-MPC and system parameters also drastically impacts the computational cost.