Stability analysis of the extended Kalman filter for Permanent Magnet Synchronous Motor

  • Djamel Taibi MSE Laboratory, University of Biskra, B.P.145, 07000, Biskra, Algeria
  • Abdenacer Titaouine MSE Laboratory, University of Biskra, B.P.145, 07000, Biskra, Algeria
  • Fateh Benchabane MSE Laboratory, University of Biskra, B.P.145, 07000, Biskra, Algeria
  • Ouafae Bennis PRISME Institute, University of Orléans, 21 rue Loigny La Bataille, 28000 Chartres, France

Abstract

This paper presents a sensorless direct field oriented control fed interior permanent magnet synchronous motor (IPMSM) by using a known mathematical tool. The Kalman filter is an observer for linear and non-linear systems and is based on the stochastic intromission, in others words, noise. It is a question of studying the state and measurement noise covariance matrices Q and R on the stability of the Extended Kalman Filter. This last is used for the d, q stator current, mechanical speed, rotor position, stator resistance and the load torque estimation. The simulation tests carried out on Matlab Simulink showed that the matrix R improves much more quality of the estimated states while the matrix Q allows the improvement of the estimation process convergence.

Author Biography

Abdenacer Titaouine, MSE Laboratory, University of Biskra, B.P.145, 07000, Biskra, Algeria
__________________
Corresponding author:
Prof. Abdenacer Titaouine
MSE Laboratory, University of Biskra, B.P.145, 07000, Biskra, Algeria
E-mail address: titaouin@yahoo.fr

 

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Published
2015-03-03
How to Cite
TAIBI, Djamel et al. Stability analysis of the extended Kalman filter for Permanent Magnet Synchronous Motor. Journal of Applied Engineering Science & Technology, [S.l.], v. 1, n. 2, p. 51-60, mar. 2015. ISSN 2352-9873. Available at: <https://revues.univ-biskra.dz/index.php/jaest/article/view/1136>. Date accessed: 28 mar. 2024.
Section
Section A: Electrical, Electronics and Automatic Engineering

Keywords

Permanent magnet synchronous machine, Direct filed oriented control, Extended Kalman filter, Estimation

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