Literature review on the control of brushless doubly-fed induction machine

Ulrich Ngnassi Nguelcheu; Ngasop Ndjiya; Eric Duckler Kenmoe Fankem; Aslain Brisco Ngnassi Djami; Golam Guidkaya; Alix Tioffo Dountio

doi:10.30574/gjeta.2023.16.3.0186

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Literature review on the control of brushless doubly-fed induction machine

Ulrich Ngnassi Nguelcheu ^{1, *}, Ngasop Ndjiya ², Eric Duckler Kenmoe Fankem ¹, Aslain Brisco Ngnassi Djami ³, Golam Guidkaya ¹ and Alix Tioffo Dountio ¹

1 Department of Physics, Faculty of science, University of Ngaoundere, Ngaoundere, Cameroon.

2 Department of Electrical Engineering, Energy and Automation, National Advanced School of Agro-Industrial Sciences, University of Ngaoundere, Ngaoundere, Cameroon.

3 Department of Fundamental Sciences and Techniques of Engineer, Chemical Engineering and Mineral Industries School, University of Ngaoundere, Ngaoundere, Cameroon.

Research Article

Global Journal of Engineering and Technology Advances, 2023, 16(03), 051–069.

Article DOI: 10.30574/gjeta.2023.16.3.0186

DOI url: https://doi.org/10.30574/gjeta.2023.16.3.0186

Publication history

Received on 25 April 2023; revised on 05 September 2023; accepted on 07 September 2023

Abstract

In recent years, dual-fed brushless asynchronous generators (BDFIG) have attracted considerable attention in variable-speed drive applications due to their simple and robust structure, good operating characteristics, and low maintenance requirements. The purpose of controlling dual-fed brushless induction generators is to achieve better performance. However, various control techniques applied to this machine have shown their limits in case of sudden fluctuations in rotor speed, relatively long response time, poor stability and high performance sensitivity to parameter fluctuations. Given its difficulty, research has focused on the most advanced technology in the world: artificial intelligence (AI). The main objective of this article is to list all the control techniques that have been applied to the BDFIG. It appears from our study that genetic algorithms as well as the multilayer perceptron have not yet been applied for the control of BDFIG.

Keywords

BDFIG; Artificial intelligence; Control techniques; Performanc

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How to cite this article

Ulrich Ngnassi Nguelcheu, Ngasop Ndjiya, Eric Duckler Kenmoe Fankem, Aslain Brisco Ngnassi Djami, Golam Guidkaya and Alix Tioffo Dountio. Literature review on the control of brushless doubly-fed induction machine. Global Journal of Engineering and Technology Advances, 2023, 16(3), 051-069. Article DOI: https://doi.org/10.30574/gjeta.2023.16.3.0186

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