Finite-Set Model Predictive Current Control of Induction Motors by Direct Use of Total Disturbance

Mahdi S. Mousavi, S. Alireza Davari, Vahab Nekoukar, Cristian Garcia, Jose Rodriguez

Research output: Contribution to journalArticlepeer-review

Abstract

Disturbance rejection strategies are very useful for the robustness improvement of the predictive control method. But they can only be used in the modulated-based predictive control methods such as continuous set model predictive control (CS-MPC) and deadbeat control. This paper presents a robust current prediction model based on total disturbance observer (TDO), which is applicable in the finite set model predictive current control (FS-MPCC). In the proposed method, the disturbance is directly used as a part of the prediction model instead of the disturbance rejection loop. So, the proposed method has two advantages over the disturbance rejection-based CS-MPC schemes. The first advantage is no need for a controller, which is an essential part of the disturbance rejection-based CS-MPC. Therefore, the proposed method is simpler and has fewer control parameters. The second feature is that the proposed model is in the stationary frame. In this way, the frame transformation is avoided in the prediction model. Moreover, to guarantee zero steady-state error in the current prediction model, this paper proposes a complete designing process for TDO based on the convergence analysis. The performance of the proposed control system is evaluated through simulations and experimental tests.

Original languageEnglish
JournalIEEE Access
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • Cost function
  • Disturbance rejection
  • FS-MPCC
  • Induction motor drive
  • Mathematical model
  • PCC
  • Predictive control
  • Predictive models
  • Robust predictive control
  • Robustness
  • Stators
  • Switches

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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