K-Best Sphere Decoding Algorithm for Long Prediction Horizon FCS-MPC | IEEE Journals & Magazine | IEEE Xplore

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


Abstract:

Finite control set model predictive control (FCS-MPC) strategies for power conversion devices benefit from extending the prediction horizon length. Solving this problem r...Show More

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.
Published in: IEEE Transactions on Industrial Electronics ( Volume: 69, Issue: 8, August 2022)
Page(s): 7571 - 7581
Date of Publication: 19 August 2021

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