Robust Scheduler Fuzzy Controller of DFIG ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
Robust Scheduler Fuzzy Controller of DFIG Wind Energy System
Auteur(s) :
Kamal, Elkhatib [Auteur]
Systèmes Tolérants aux Fautes [STF]
Oueidat, Mohamad [Auteur]
Aitouche, Abdel [Auteur]
Systèmes Tolérants aux Fautes [STF]
Ghorbani, Reza [Auteur]
Systèmes Tolérants aux Fautes [STF]
Oueidat, Mohamad [Auteur]
Aitouche, Abdel [Auteur]
Systèmes Tolérants aux Fautes [STF]
Ghorbani, Reza [Auteur]
Titre de la revue :
IEEE Transactions on Sustainable Energy
Pagination :
1-10
Éditeur :
IEEE
Date de publication :
2013-02-26
ISSN :
1949-3029
Mot(s)-clé(s) en anglais :
Doubly-fed induction generator (DFIG)
fuzzy controller
fuzzy observer
linear matrix inequalities
LMIs
parameters uncertaintie
wind energy systems
WES
fuzzy controller
fuzzy observer
linear matrix inequalities
LMIs
parameters uncertaintie
wind energy systems
WES
Discipline(s) HAL :
Sciences de l'ingénieur [physics]/Automatique / Robotique
Résumé en anglais : [en]
This paper addresses the robust fuzzy scheduler controller (RFSC) for nonlinear systems which is robust enough to stabilize a nonlinear system with parametric uncertainties, wind disturbance, and give an acceptable closed-loop ...
Lire la suite >This paper addresses the robust fuzzy scheduler controller (RFSC) for nonlinear systems which is robust enough to stabilize a nonlinear system with parametric uncertainties, wind disturbance, and give an acceptable closed-loop performance in the presence of state variables unavailable for measurements. The Takagi-Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the nonlinear system. The concept of parallel distributed compensation (PDC) is employed to design fuzzy control from the TS fuzzy models. Sufficient conditions are formulated in the format of linear matrix inequalities (LMIs). The proposed controller design methodology is finally demonstrated through the model of wind energy systems (WES) with a doubly-fed induction generator (DFIG) to illustrate the effectiveness of the proposed method. The proposed algorithm maximizes the produced power and is able to maintain a stable system during the parameter uncertainties.Lire moins >
Lire la suite >This paper addresses the robust fuzzy scheduler controller (RFSC) for nonlinear systems which is robust enough to stabilize a nonlinear system with parametric uncertainties, wind disturbance, and give an acceptable closed-loop performance in the presence of state variables unavailable for measurements. The Takagi-Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the nonlinear system. The concept of parallel distributed compensation (PDC) is employed to design fuzzy control from the TS fuzzy models. Sufficient conditions are formulated in the format of linear matrix inequalities (LMIs). The proposed controller design methodology is finally demonstrated through the model of wind energy systems (WES) with a doubly-fed induction generator (DFIG) to illustrate the effectiveness of the proposed method. The proposed algorithm maximizes the produced power and is able to maintain a stable system during the parameter uncertainties.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
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