FPGA-Implementation Friendly Long-Horizon Finite Control Set Model Predictive Control for High-Power Electronic Systems

Stefan Baltruweit, Eyke Liegmann, Petros Karamanakos, Ralph Kennel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

In this paper we present a branch-and-bound algorithm that facilitates the real-time implementation of long-horizon finite control set model predictive control (FCS-MPC) for high-power electronic systems. To achieve this, the optimization process is modified such that the more likely candidates (i.e., the switching sequences with less switching transitions) are explored first. By doing so, computational demanding operations can be efficiently pipelined in a field-programmable gate array (FPGA), rendering the proposed method computationally feasible. The effectiveness of the introduced method is tested both in an FPGA-in-the-loop simulation and with a real-world setup based on a scaled-down low-voltage variable speed drive system consisting of a three-level neutral point clamped inverter and an induction machine. As shown, a real-time implementation with horizon length of twelve is achieved without sacrificing optimality.

Original languageEnglish
Title of host publicationProceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1823-1828
Number of pages6
ISBN (Electronic)9781728163444
DOIs
StatePublished - 24 May 2021
Event12th IEEE Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021 - Virtual, Singapore, Singapore
Duration: 24 May 202127 May 2021

Publication series

NameProceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021

Conference

Conference12th IEEE Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
Country/TerritorySingapore
CityVirtual, Singapore
Period24/05/2127/05/21

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