By Topic

Artificial intelligence applications in direct torque control

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

2 Author(s)
Cruz, P.P. ; Inst. Tecnologico y de Estudios Superiores de Monterrey, Mexico ; Paredes, J.P.S.

The purpose of this paper is to show a new direct torque control (DTC) scheme that allows to improve the performance of a sensorless induction motor (IM) speed control in terms of less stator flux and currents distortions, keeping a constant switching frequency in the inverter. It is also shown a fuzzy logic application for tuning the PI speed controller, The work proposes a complete DTC scheme using two different stator resistance estimators, one of them is a neural network (ANN) and the other one is an adaptive neuro-fuzzy methodology to build a sugeno fuzzy estimator. Experimental and simulation results have been carried out, showing the advantages of the new scheme.

Published in:

Power Electronics and Drive Systems, 2003. PEDS 2003. The Fifth International Conference on  (Volume:2 )

Date of Conference:

17-20 Nov. 2003