• DocumentCode
    2499128
  • Title

    Design of Kalman Filter for induction motor drive

  • Author

    Singh, Karam ; Singh, Monika

  • Author_Institution
    Dept. of Electr. Eng., Indian Inst. of Technol., Roorkee, Roorkee, India
  • fYear
    2013
  • fDate
    12-14 April 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper compares the standard and extended versions of kalman filter for rotor flux estimation in a voltage source inverter fed vector controlled induction motor drive. The design method for the both versions of kalman filter is presented and shown. Only simulation results are presented in this paper. Methodology to create KF, EKF for online identification of induction motor parameters are also described in details. The Extended Kalman Filter can be used for combined state and parameter estimation by treating selected parameters as extra states and forming an augmented state vector. Depending on whether the original state space model is linear or not, the augmented model is nonlinear in multiplication of states. A fifth order augmented state space model is developed when the EKF is applied to the simultaneous estimation of states of stator and rotor d-q current and rotor d-q fluxes. Important conclusions, together with recommendations for observer selection.
  • Keywords
    Kalman filters; induction motor drives; invertors; machine vector control; parameter estimation; rotors; stators; extended Kalman filter; fifth order augmented state space model; induction motor parameters; parameter estimation; rotor d-q current; rotor d-q flux; rotor flux estimation; vector controlled induction motor drive; voltage source inverter; Current measurement; Kalman filters; Mathematical model; Noise; Noise measurement; Rotors; Stators; Extended kalman filter; Gaussian noise; Induction motor parameters; Kalman filter; On-line estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering and Systems (SCES), 2013 Students Conference on
  • Conference_Location
    Allahabad
  • Print_ISBN
    978-1-4673-5628-2
  • Type

    conf

  • DOI
    10.1109/SCES.2013.6547575
  • Filename
    6547575