• DocumentCode
    3587053
  • Title

    BLDCM speed observer based on scale-corrected minimal skew simplex sampling UKF

  • Author

    Zhugang Ding ; Guoliang Wei

  • Author_Institution
    Dept. of Control Sci. & Eng., Univ. of Shanghai for Sci. & Technol., Shanghai, China
  • fYear
    2014
  • Firstpage
    2169
  • Lastpage
    2173
  • Abstract
    In this paper, a scale-corrected minimal skew simplex sampling UKF algorithm for BLDCM sensorless control has been studied to cancel the position sensor by use of a systematical, analytical approach. Compared with general UKF, to reduce amount of computation and increase the estimation precision, the sampling method with the least Sigma points called minimal skew simplex sampling is adopted. Moreover, the scale-corrected strategy is introduced into the minimal skew simplex sampling UKF to overcome the nonlocal effects. On the other hand, for more easily calculating the value of back-EMF, the shape function of counter electromotive force is approximated by a series of sine and cosine functions based on the law of Fourier series. Finally, the effectiveness of proposed sensorless technique is verified through simulation in MATLAB/Simulink, which is validated by complete simulation results on BLDCM.
  • Keywords
    Fourier series; Kalman filters; angular velocity control; brushless DC motors; nonlinear filters; sampling methods; sensorless machine control; BLDCM sensorless control; BLDCM speed observer; Fourier series; cosine functions; counter electromotive force; estimation precision; least sigma points; sampling method; scale-corrected minimal skew simplex sampling UKF algorithm; scale-corrected strategy; shape function; Estimation; Noise; Rotors; Sampling methods; Sensorless control; Torque; Windings;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Biomimetics (ROBIO), 2014 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ROBIO.2014.7090658
  • Filename
    7090658