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

Julio Viola; Jose Restrepo; Jose Aller

doi:10.1109/ISIE.2015.7281513

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

Julio Viola
, Jose Restrepo
, Jose Aller

Research Group in Energy (GIE)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Proceedings - 2015 IEEE 24th International Symposium on Industrial Electronics, ISIE 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	468-475
Number of pages	8
ISBN (Electronic)	9781467375542
DOIs	https://doi.org/10.1109/ISIE.2015.7281513
State	Published - 28 Sep 2015
Event	24th IEEE International Symposium on Industrial Electronics, ISIE 2015 - Buzios, Rio de Janeiro, Brazil Duration: 3 Jun 2015 → 5 Jun 2015

Publication series

Name	IEEE International Symposium on Industrial Electronics
Volume	2015-September

Conference

Conference	24th IEEE International Symposium on Industrial Electronics, ISIE 2015
Country/Territory	Brazil
City	Buzios, Rio de Janeiro
Period	3/06/15 → 5/06/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Backpropagation
Induction motor drives
Lyapunov methods
Neural Networks

CACES Knowledge Areas

317A Electricity and Energy

Access to Document

10.1109/ISIE.2015.7281513

Cite this

Viola, J., Restrepo, J., & Aller, J. (2015). Current controller for induction motor using an Artificial Neural Network trained with a Lyapunov based algorithm. In Proceedings - 2015 IEEE 24th International Symposium on Industrial Electronics, ISIE 2015 (pp. 468-475). Article 7281513 (IEEE International Symposium on Industrial Electronics; Vol. 2015-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIE.2015.7281513

Viola, Julio ; Restrepo, Jose ; Aller, Jose. / Current controller for induction motor using an Artificial Neural Network trained with a Lyapunov based algorithm. Proceedings - 2015 IEEE 24th International Symposium on Industrial Electronics, ISIE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 468-475 (IEEE International Symposium on Industrial Electronics).

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

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.",

keywords = "Backpropagation, Induction motor drives, Lyapunov methods, Neural Networks",

author = "Julio Viola and Jose Restrepo and Jose Aller",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 24th IEEE International Symposium on Industrial Electronics, ISIE 2015 ; Conference date: 03-06-2015 Through 05-06-2015",

year = "2015",

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doi = "10.1109/ISIE.2015.7281513",

language = "English",

series = "IEEE International Symposium on Industrial Electronics",

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Viola, J, Restrepo, J & Aller, J 2015, Current controller for induction motor using an Artificial Neural Network trained with a Lyapunov based algorithm. in Proceedings - 2015 IEEE 24th International Symposium on Industrial Electronics, ISIE 2015., 7281513, IEEE International Symposium on Industrial Electronics, vol. 2015-September, Institute of Electrical and Electronics Engineers Inc., pp. 468-475, 24th IEEE International Symposium on Industrial Electronics, ISIE 2015, Buzios, Rio de Janeiro, Brazil, 3/06/15. https://doi.org/10.1109/ISIE.2015.7281513

Current controller for induction motor using an Artificial Neural Network trained with a Lyapunov based algorithm. / Viola, Julio; Restrepo, Jose; Aller, Jose.
Proceedings - 2015 IEEE 24th International Symposium on Industrial Electronics, ISIE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 468-475 7281513 (IEEE International Symposium on Industrial Electronics; Vol. 2015-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Current controller for induction motor using an Artificial Neural Network trained with a Lyapunov based algorithm

AU - Viola, Julio

AU - Restrepo, Jose

AU - Aller, Jose

PY - 2015/9/28

Y1 - 2015/9/28

N2 - 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.

AB - 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.

KW - Backpropagation

KW - Induction motor drives

KW - Lyapunov methods

KW - Neural Networks

UR - https://www.scopus.com/pages/publications/84947241687

U2 - 10.1109/ISIE.2015.7281513

DO - 10.1109/ISIE.2015.7281513

M3 - Conference contribution

AN - SCOPUS:84947241687

T3 - IEEE International Symposium on Industrial Electronics

SP - 468

EP - 475

BT - Proceedings - 2015 IEEE 24th International Symposium on Industrial Electronics, ISIE 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 24th IEEE International Symposium on Industrial Electronics, ISIE 2015

Y2 - 3 June 2015 through 5 June 2015

ER -

Viola J, Restrepo J, Aller J. Current controller for induction motor using an Artificial Neural Network trained with a Lyapunov based algorithm. In Proceedings - 2015 IEEE 24th International Symposium on Industrial Electronics, ISIE 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 468-475. 7281513. (IEEE International Symposium on Industrial Electronics). doi: 10.1109/ISIE.2015.7281513

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

Abstract

Publication series

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Bibliographical note

Keywords

CACES Knowledge Areas

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