Event-Triggered Model Predictive Control for Power Converters

Benfei Wang, Jingjing Huang, Changyun Wen, Jose Rodriguez, Cristian Garcia, Hoay Beng Gooi, Zheng Zeng

Research output: Contribution to journalArticlepeer-review

56 Citations (Scopus)


In this letter, an event-triggered model predictive control (ET-MPC) method for power converters is presented. In the proposed method, the model predictive control (MPC) scheme is triggered only when the state of the converter exceeds a preset threshold; otherwise, the MPC scheme is suspended and the control signal is held as constant. Therefore, compared with the conventional MPC with finite control set (FCS-MPC), the ET-MPC method has the advantages of less computational burden and less switching actions, which contribute to lower switching losses, while ensuring satisfactory regulation performance. A buck converter prototype is adopted to validate the performance of ET-MPC. The results from the comparison with FCS-MPC demonstrate the effectiveness of the proposed ET-MPC method.

Original languageEnglish
Article number8948314
Pages (from-to)715-720
Number of pages6
JournalIEEE Transactions on Industrial Electronics
Issue number1
Publication statusPublished - Jan 2021


  • Computational requirement
  • event-triggered (ET) control
  • model predictive control (MPC)
  • switching loss

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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