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A review of finite control set model predictive control for linear machines

  • Wei Xu
  • , Han Xiao*
  • , Yirong Tang
  • , Jian Ge
  • , Leilei Guo
  • , Abdul Khalique Junejo
  • *Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

10 Scopus citations

Abstract

Linear machines (LMs) have become excellent candidates for linear motion applications due to their abilities of generating thrust without any transmissions, and have been widely adopted in transportation, industries etc. Among the numerous control methods of LM drive systems, finite control set model predictive control (FCS-MPC) method has been given special attention due to its clear concept, fast response performance, and ability to handle constrained multivariate non-linear control problems. It is widely used to improve the performance and efficiency of overall LM drive systems. Firstly, based on the three elements of FCS-MPC, the advantages and shortcomings of the FCS-MPC method in applications are fully investigated. The research status in FCS-MPC has been summarised, such as multistep MPC, parameters robustness improvement, fast optimisation, and multi-vector MPC. Then, the key issues in FCS-MPC such as delay compensation, parameters design, and stability analysis are discussed, and their typical research methods and current research status are explained. Finally, the future development trends of FCS-MPC in LM drive systems are discussed.

Original languageEnglish
Pages (from-to)1567-1583
Number of pages17
JournalIET Electric Power Applications
Volume18
Issue number11
DOIs
StatePublished - Nov 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2024 The Author(s). IET Electric Power Applications published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

Keywords

  • fast optimization
  • finite control set model predictive control
  • linear machines
  • multi-vector model predictive control
  • parameters robustness

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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