Design of Fast Model Predictive Controller for Permanent Magnet Synchronous Motor Drive System

Qian Guo, Qinyao Liu, Zhimin Cao

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

Abstract

In this article, a new predictive controller based on fast model predictive control has been proposed for permanent magnet synchronous motor(PMSM) drive system to solve the quadratic programming problem online in a very short period. The mathematical model of PMSM has been described in terms of state space and discretized by Euler method firstly. Then, the discrete model is linearized at the steady state point. Based on this, the optimization objective function which is used to measure the performance of the PMSM is designed properly. The approximate primal barrier interior point method is employed to speed up the optimization process. Finally, the simulation results declare that the proposed algorithm is useful for PMSM drive system. In addition, the proposed approach enables the model parameters, the horizon size as well as the weighting factors updated in real time so that it has potential to solve problems such as model mismatch in the future.

Original languageEnglish
Title of host publication2023 42nd Chinese Control Conference, CCC 2023
PublisherIEEE Computer Society
Pages2776-2781
Number of pages6
ISBN (Electronic)9789887581543
DOIs
Publication statusPublished - 2023
Event42nd Chinese Control Conference, CCC 2023 - Tianjin, China
Duration: 24 Jul 202326 Jul 2023

Publication series

NameChinese Control Conference, CCC
Volume2023-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference42nd Chinese Control Conference, CCC 2023
Country/TerritoryChina
CityTianjin
Period24/07/2326/07/23

Keywords

  • Fast model predictive control
  • approximate primal barrier interior point method
  • continuous control set model predictive control
  • permanent magnet synchronous motors
  • quadratic programming

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