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Retracted

Advances in Fuzzy Systems has retracted this article. The article was previously published as “Loukal Keltoum, Benalia Leila, “Type-2 Fuzzy Logic Control of a Doubly-Fed Induction Machine (DFIM),” International Journal of Artificial Intelligence, Vol 4, No 4, 2015. http://iaescore.com/journals/index.php/IJAI/article/view/6125 [2].

The authors say they did not approve final publication in International Journal of Artificial Intelligence and they do not support the retraction. The IJAI Editor-in-Chief said this was the responsibility of journal staff, but the journal and publisher did not respond to our queries.

View the full Retraction here.

References

  1. K. Loukal and L. Benalia, “Type-2 fuzzy logic controller of a doubly fed induction machine,” Advances in Fuzzy Systems—Applications and Theory, vol. 2016, Article ID 8273019, pp. 1–10, 2016.
  2. L. Keltoum and B. Leila, “Type-2 fuzzy logic control of a doubly-fed induction machine (DFIM),” International Journal of Artificial Intelligence, vol. 4, no. 4, 2015, http://iaescore.com/journals/index.php/IJAI/article/view/6125.
Advances in Fuzzy Systems
Volume 2016, Article ID 8273019, 10 pages
http://dx.doi.org/10.1155/2016/8273019
Research Article

Type-2 Fuzzy Logic Controller of a Doubly Fed Induction Machine

LGE Research Laboratory, Department of Electrical Engineering, Faculty of Technology, Mohamed Boudiaf University of M’sila, BP 166, Ichbilia, 28000 M’sila, Algeria

Received 24 October 2015; Revised 22 December 2015; Accepted 29 December 2015

Academic Editor: Mehmet Onder Efe

Copyright © 2016 Keltoum Loukal and Leila Benalia. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Interval type-2 fuzzy logic controller (IT2FLC) method for controlling the speed with a direct stator flux orientation control of doubly fed induction motor (DFIM) is proposed. The fuzzy controllers have demonstrated their effectiveness in the control of nonlinear systems, and in many cases it is proved that their robustness and performance are less sensitive to parameters variation over conventional controllers. The synthesis of stabilizing control laws design based on IT2FLC is developed. A comparative analysis between type-1 fuzzy logic controller (T1FLC) and IT2FLC of the DFIM is shown. Simulation results show the feasibility and the effectiveness of the suggested method to the control of the DFIM under different operating conditions such as load torque and in the presence of parameters variation.