Speed estimation of an induction motor drive using extended Kalman filter

K. L. Shi, T. F. Chan, Y. K. Wong, Siu Lau Ho

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

27 Citations (Scopus)


This paper presents a detailed study of the extended Kalman filter (EKF) far estimating the rotor speed of an induction motor drive. The general structure of the Kalman filter is reviewed and the various system vectors and matrices are defined. By including the rotor speed as a state variable, the EKF equations are established from a discrete two-axis model of the three-phase induction motor. Using the software MATLAB/Simulink, simulation of the EKF speed estimation algorithm is carried out for an induction motor drive with constant V/Hz frequency control and an induction motor drive with direct self control. The investigations show that the EKF is capable of tracking the actual rotor speed provided that the elements of the covariance matrices are properly selected. Moreover, the performance of the EKF is satisfactory even in the presence of noise or when there are variations in the induction machine parameters.
Original languageEnglish
Title of host publication2000 IEEE Power Engineering Society, Conference Proceedings
Number of pages6
ISBN (Electronic)0780359356, 9780780359352
Publication statusPublished - 1 Jan 2000
EventIEEE Power Engineering Society Winter Meeting, 2000 - Singapore, Singapore
Duration: 23 Jan 200027 Jan 2000


ConferenceIEEE Power Engineering Society Winter Meeting, 2000


  • Induction motor drives
  • Kalman filter
  • sensorless control

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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