By Topic

Methodological Insights for Online Estimation of Induction Motor Parameters

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Laroche, E. ; CNRS, Univ. Louis Pasteur, Illkirch ; Sedda, E. ; Durieu, C.

This paper presents contributions for online estimation of states and parameters of an induction motor with Kalman filter. In order to ensure a good level of confidence of the estimation, a suitable methodology is proposed and two of its main points are investigated. First, an original method is used for tuning the covariance matrices, relying on the evaluation of the state noise due to modeling errors. Second, an observability analysis is developed, allowing to validate the model and the proposed excitation trajectory. Experimental results show that, with the chosen input signal, the parameters can be estimated with good accuracy in less than two seconds.

Published in:

Control Systems Technology, IEEE Transactions on  (Volume:16 ,  Issue: 5 )