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
Link To Document