Current controller for induction motor using an Artificial Neural Network trained with a Lyapunov based algorithm

Julio Viola, Jose Restrepo, Jose Aller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents the use of a training algorithm based on a Lyapunov function approach applied to a stator current controller based on a state variable description of the induction machine plus a reference model. The results obtained with the proposed controller are compared with a previously reported method based on a Nonlinear Auto-Regressive Moving Average with eXogenous inputs (NARMAX) description of the induction machine. The proposed Lyapunov based training algorithm is used to ensure convergence of the weights towards a global minimum in the error function. Real time simulations employing a DSP based test bench are used to test the validity of the algorithms and the results are verified by a practical implementation of these controllers.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE 24th International Symposium on Industrial Electronics, ISIE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages468-475
Number of pages8
ISBN (Electronic)9781467375542
DOIs
StatePublished - 28 Sep 2015
Event24th IEEE International Symposium on Industrial Electronics, ISIE 2015 - Buzios, Rio de Janeiro, Brazil
Duration: 3 Jun 20155 Jun 2015

Publication series

NameIEEE International Symposium on Industrial Electronics
Volume2015-September

Conference

Conference24th IEEE International Symposium on Industrial Electronics, ISIE 2015
Country/TerritoryBrazil
CityBuzios, Rio de Janeiro
Period3/06/155/06/15

Keywords

  • Backpropagation
  • Induction motor drives
  • Lyapunov methods
  • Neural Networks

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