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

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...

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Bibliographic Details
Published inIEEE transactions on industrial electronics (1982) Vol. 64; no. 2; pp. 935 - 947
Main Authors Vazquez, Sergio, Rodriguez, Jose, Rivera, Marco, Franquelo, Leopoldo G., Norambuena, Margarita
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
AC–DC power conversion
Algorithms
Control systems
Cost function
dc–ac power conversion
Electronic systems
Optimization
Power converters
Power electronics
Prediction algorithms
Prediction models
Predictive control
Predictive models
Trends
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Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2016.2625238