Hybrid Sphere Decoder for Long Prediction Horizon FCS-MPC

In finite control set model predictive control strategies, extending the prediction horizon length provides important closed-loop performance improvements. However, the computational costs are increased in exponential fashion. Transforming the problem to an equivalent box-constrained integer least-s...

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Detalles Bibliográficos
Autores: Zafra, Eduardo, Vázquez Pérez, Sergio, Márquez Alcaide, Abraham, Pérez Martín, Emilia, García Franquelo, Leopoldo, León Galván, José Ignacio
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2022
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/173968
Acceso en línea:https://hdl.handle.net/11441/173968
https://doi.org/10.1109/TIE.2022.3194587
Access Level:acceso abierto
Palabra clave:DC–AC power conversion
digital control
predictive control
Descripción
Sumario:In finite control set model predictive control strategies, extending the prediction horizon length provides important closed-loop performance improvements. However, the computational costs are increased in exponential fashion. Transforming the problem to an equivalent box-constrained integer least-squares formulation enables the usage of sphere decoding algorithms (SDA) that can efficiently solve this problem. Recently, a K-best sphere decoder was proposed and designed for hardware platforms. This algorithm follows a breadth-first strategy different to the conventional SDA. In this work, a hybrid SDA that combines the merits of both the K-best SDA and the conventional SDA is proposed with the objective of increasing optimality likelihood and improve control performance. In particular, it is proposed that a K-best sphere decoder delivers a preliminary optimal solution. Then, a conventional SDA uses the available calculation time to search for a better solution. Simulation and experimental results confirm the validity of the proposal in terms of performance and computational efficiency.