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Model Predictive Control for Power Converters and Drives: Advances and Trends

 

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Author: Vázquez Pérez, Sergio
Rodríguez, José
Rivera, Marco
García Franquelo, Leopoldo
Norambuena, Margarita
Department: Universidad de Sevilla. Departamento de Ingeniería Electrónica
Date: 2017-02
Published in: IEEE Transactions on Industrial Electronics, 64 (2), 935-947.
Document type: Article
Abstract: Model predictive control (MPC) is a very attractive solution for controlling power electronic converters. The aim of this paper is to present and discuss the latest developments in MPC for power converters and drives, describing the current state of this control strategy and analyzing the new trends and challenges it presents when applied to power electronic systems. The paper revisits the operating principle of MPC and identifies three key elements in the MPC strategies, namely the prediction model, the cost function, and the optimization algorithm. This paper summarizes the most recent research concerning these elements, providing details about the different solutions proposed by the academic and industrial communities
Cite: Vázquez, S., Rodríguez, J., Rivera, M., Franquelo, Leopoldo G. y Norambuena, M. (2017). Model Predictive Control for Power Converters and Drives: Advances and Trends. IEEE Transactions on Industrial Electronics, 64 (2), 935-947.
Size: 1.087Mb
Format: PDF

URI: https://hdl.handle.net/11441/80174

DOI: 10.1109/TIE.2016.2625238

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