• DocumentCode
    1911661
  • Title

    State estimation of induction motor using unscented Kalman filter

  • Author

    Akin, Bilal ; Orguner, Umut ; Ersak, Aydin

  • Author_Institution
    Dept. of Electr. & Elelctronics Eng., Middle East Tech. Univ., Ankara, Turkey
  • Volume
    2
  • fYear
    2003
  • fDate
    23-25 June 2003
  • Firstpage
    915
  • Abstract
    In this paper, a new estimation technique unscented Kalman filter (UKF) is applied to state observation in field oriented control (FOC) of induction motor. UKF, a recent derivative-free nonlinear estimation tool, is used for estimating rotor speed and fluxes using sensed stator current and voltages. In the simulations, UKF, whose several intrinsic properties suggest its use over EKF in highly nonlinear systems, turned out to be very similar to EKF in flux estimates. The simulation results also show that UKF has slightly better speed estimation performance than EKF while driven under the identical machine model and parameters (covariances).
  • Keywords
    Kalman filters; induction motors; machine vector control; nonlinear control systems; nonlinear estimation; observers; derivative free nonlinear estimation tool; extended Kalman filter; field oriented control; flux estimation; induction motor; nonlinear systems; rotor speed estimation; sensorless vector control; state estimation; state observer; unscented Kalman filter; Filtering; Induction machines; Induction motors; Noise measurement; Nonlinear equations; Nonlinear filters; Rotors; Size measurement; State estimation; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Applications, 2003. CCA 2003. Proceedings of 2003 IEEE Conference on
  • Print_ISBN
    0-7803-7729-X
  • Type

    conf

  • DOI
    10.1109/CCA.2003.1223132
  • Filename
    1223132