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K-Best Sphere Decoding Algorithm for Long Prediction Horizon FCS-MPC

Eduardo Zafra, Sergio Vázquez, Abraham Marquez, Leopoldo G. Franquelo, José I. Leon, Emilia Perez Martin

2021IEEE Transactions on Industrial Electronics43 citationsDOI

Abstract

Finite control set model predictive control (FCS-MPC) strategies for power conversion devices benefit from extending the prediction horizon length. Solving this problem relies on the definition of the underlying integer least-squares problem. Sphere decoding algorithm (SDA) has been extensively used in previous works as an approach to solve this problem. In this article, a parallel and fully scalable K-best SDA hardware design is proposed as an alternative. The K-best SDA establishes a different breadth-first search strategy, which addresses some of the main drawbacks of the SDA. Through experimental tests based on an uninterruptible power supply, the K-best SDA performance for long prediction horizon FCS-MPC is assessed and verified. Results demonstrate key beneficial aspects through which the K-best SDA is capable of rendering an improved control performance when compared to the conventional SDA.

Topics & Concepts

Model predictive controlDecoding methodsScalabilityComputer scienceHorizonAlgorithmMathematical optimizationControl (management)MathematicsArtificial intelligenceGeometryDatabaseMultilevel Inverters and ConvertersAdvanced DC-DC ConvertersMicrogrid Control and Optimization