• DocumentCode
    2065231
  • Title

    T-S fuzzy modeling of interior permanent magnet synchronous motor

  • Author

    Wang, Fa Guang ; Park, Seung Kyu ; Yoon, Taesung ; Ahn, Ho Kyun

  • Author_Institution
    Dept. of Electr. Eng., Changwon Nat. Univ., Changwon, South Korea
  • fYear
    2010
  • fDate
    Nov. 29 2010-Dec. 1 2010
  • Firstpage
    182
  • Lastpage
    186
  • Abstract
    Control of interior permanent magnet (IPMSM) is difficult because its nonlinearity and parameter uncertainty. In this paper, a fuzzy c-regression models clustering algorithm which is based on T-S fuzzy is used to model IPMSM with a series linear model and weight them by memberships. Lagrangian of constrained function is built for calculating clustering centers where training output data are considered. Based on these clustering centers, least square method is applied for T-S fuzzy linear model parameters. As a result, IPMSM can be modeled as T-S fuzzy model for T-S fuzzy control of them.
  • Keywords
    fuzzy set theory; permanent magnet motors; regression analysis; T-S fuzzy modeling; constrained function; fuzzy c-regression model; parameter uncertainty; permanent magnet synchronous motor; series linear model; IPMSM; T-S fuzzy model; feedback; identification; linear model; nonlinear system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on
  • Conference_Location
    Cairo
  • Print_ISBN
    978-1-4244-8134-7
  • Type

    conf

  • DOI
    10.1109/ISDA.2010.5687268
  • Filename
    5687268