Research of PMSM modeling based on least square support vector machines

Jun Zhao, Weiguo Liu, Bo Tan

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

Abstract

A modeling approach based on least square support vector machine (LSSVM) had been applied for permanent magnet synchronous motor (PMSM) and inverter with PMSM, which was multi-variable, nonlinear and coupled system. The modeling parameters with RBF kernel function was optimized by using cross validation method. The simulation result show that the tow modeling method is very effective. The maximum root mean square error (RMSE) of modeling of PMSM is 0.3196 and the maximum relative error is 0.2341%. And the maximum RMSE of modeling of inverter with PMSM is 0.4421 and the maximum relative error is 2.4121%. Using LSSVM for modeling of PMSM performs better forecast accuracy and successful modeling of PMSM.

Original languageEnglish
Title of host publicationProceedings - International Conference on Electrical and Control Engineering, ICECE 2010
Pages4039-4045
Number of pages7
DOIs
StatePublished - 2010
EventInternational Conference on Electrical and Control Engineering, ICECE 2010 - Wuhan, China
Duration: 26 Jun 201028 Jun 2010

Publication series

NameProceedings - International Conference on Electrical and Control Engineering, ICECE 2010

Conference

ConferenceInternational Conference on Electrical and Control Engineering, ICECE 2010
Country/TerritoryChina
CityWuhan
Period26/06/1028/06/10

Keywords

  • Least square support vector machine
  • Modeling
  • Permanent magnet synchronous motor

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