• DocumentCode
    128240
  • Title

    On-line parameter identification of asynchronous motor using improved least squares

  • Author

    Guo Jiantao ; Li Guoli ; Xie Fang ; Hu Cungang ; Pan Zhifeng ; Meng Nan

  • Author_Institution
    Sch. of Electr. Eng. & Autom., Anhui Univ., Hefei, China
  • fYear
    2014
  • fDate
    9-11 June 2014
  • Firstpage
    130
  • Lastpage
    134
  • Abstract
    The value of stator and rotor resistance, inductance is important to controller design and condition monitoring of an asynchronous motor system. This paper proposes an improved least squarest to identify the parameters of asynchronous motor. Instead of using signal of rotor magnetic linkage, we measuring the stator current, voltage and signal of rotational speed, made use of the method of forgetting factor recursive least squares to carry on recognizing motor parameters.
  • Keywords
    induction motors; least squares approximations; parameter estimation; rotors; stators; asynchronous motor; least squares; magnetic linkage; on-line parameter identification; rotor; stator; Educational institutions; Equations; Mathematical model; Parameter estimation; Rotors; Stator windings; asynchronous motor; forgetting factor recursive least squares; parameter identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4799-4316-6
  • Type

    conf

  • DOI
    10.1109/ICIEA.2014.6931145
  • Filename
    6931145