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Titre: Dynamic Performance Improvement of DFIM based on Hybrid Computational Technique
Auteur(s): Zidani, Mohamed Yazid
Brakta, Noureddine
Bendjeghaba, Omar
Mots-clés: DFIM
Decoupling Control
PI
AI
ANNC
Date de publication: 2021
Editeur: IEEE
Collection/Numéro: 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC);
Résumé: This paper presents a hybrid intelligent nonlinear control, based on particle swarm optimization (PSO) technique and artificial intelligence controller (AI) to improve the dynamic performance of the system. These controllers are destined for the speed control of Doubly Fed Induction Motor (DFIM). The proportional-integral controller for speed regulation of the induction motor is the most extensively used controller. However, given the various operating conditions and the nature of parameter variability, the PI controller has some drawbacks. So, one of the frequently discussed applications of artificial intelligence (AI) in control is the replacement of a proportional integral speed controller with Artificial Neural Network (ANN) speed controller but the choice of the gain’s parameters controller is one of the main problems. So, Particle Swarm Optimization (PSO) technique on optimization performance is added to the PI and ANN controllers to find the best gain values. The simulation results for different scenarios illustrate the high performance of the proposed artificial intelligence controller for DFIM running at variable speeds in terms of consistency and stability
URI/URL: DOI: 10.1109/CCWC51732.2021.9376017
https://ieeexplore.ieee.org/abstract/document/9376017
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/6682
ISBN: Electronic ISBN:978-1-6654-1490-6
Print on Demand(PoD) ISBN:978-1-6654-3058-6
Collection(s) :Communications Internationales

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