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This research has been partially funded by the project PID2022-137593OBI00, financed by the Spanish Ministry MCIN/AEI/10.13039/501100011033/FEDER, UE, and FSE+.

Analysis of institutional authors

Purraji, MarziyeCorresponding AuthorZamiri, ElyasAuthorDe Castro, AngelAuthor

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February 24, 2025
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Easy and Straightforward FPGA Implementation of Model Predictive Control Using HDL Coder

Publicated to:Electronics. 14 (3): 419- - 2025-02-01 14(3), DOI: 10.3390/electronics14030419

Authors: Purraji, Marziye; Zamiri, Elyas; de Castro, Angel

Affiliations

Univ Autonoma Madrid, HCTLab Res Grp, Madrid 28049, Spain - Author

Abstract

Model Predictive Control (MPC) is widely adopted for power electronics converters due to its ability to optimize system performance under dynamic constraints. However, its FPGA implementation remains challenging due to the complexity of Hardware Description Language (HDL) programming. This paper addresses this challenge by introducing a straightforward methodology that simplifies FPGA implementation using MATLAB R2022b Simulink HDL Coder. It is shown that HDL Coder yields favorable synthesis outcomes, both in terms of area and time, compared to hand-coded HDL. Notably, the proposed method achieves a significantly reduced sampling step for the MPC algorithm-down to 32 ns-marking a substantial improvement over state-of-the-art implementations. The Integrated Logic Analyzer (ILA) IP available in the Vivado tool is used during the HIL testing phase to facilitate the real-time observation and analysis required for debugging and confirming the FPGA-implemented controller performance. Additionally, this paper discusses the advantages of utilizing HDL Coder for simplifying the FPGA programming process in power electronics applications and addresses the design challenges encountered using this methodology.

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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-18:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 1 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

    Leadership analysis of institutional authors

    There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (PURRAJI, MARZIYE) and Last Author (DE CASTRO MARTIN, ANGEL).

    the author responsible for correspondence tasks has been PURRAJI, MARZIYE.