Real-time implementation of Bi input-extended Kalman filter-based estimator for speed-sensorless control of induction motors

Barut M., DEMİR R., ZERDALİ E., İNAN R.

IEEE Transactions on Industrial Electronics, cilt.59, sa.11, ss.4197-4206, 2012 (SCI-Expanded, Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 59 Sayı: 11
  • Basım Tarihi: 2012
  • Doi Numarası: 10.1109/tie.2011.2178209
  • Dergi Adı: IEEE Transactions on Industrial Electronics
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.4197-4206
  • Anahtar Kelimeler: Extended Kalman filter, induction motors (IMs), load torque estimation, rotor and stator resistance estimation, sensorless control
  • Isparta Uygulamalı Bilimler Üniversitesi Adresli: Evet

Özet

This paper presents the real-time implementation of a bi input-extended Kalman filter (EKF) (BI-EKF)-based estimator in order to overcome the simultaneous estimation problem of the variations in stator resistance R s and rotor resistance R′ r aside from the load torque t L and all states required for the speed-sensorless control of induction motors (IMs) in the wide speed range. BI-EKF algorithm consists of a single EKF algorithm using consecutively two inputs based on two extended IM models developed for the simultaneous estimation of R′ r and R s. Therefore, from the point of real-time implementation, it requires less memory than previous EKF-based studies exploiting two separate EKF algorithms for the same aim. By using the measured stator phase voltages and currents, the developed estimation algorithm is tested with real-time experiments under challenging variations of R s , R′ r, and t L in a wide speed range; the results obtained from BI-EKF reveal significant improvement in the all estimated states and parameters when compared with those of the single EKFs estimating only R′ r or R s. © 2011 IEEE.