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Modeling and control of Double Star PMSG connected to standalone DC network

In this paper, we apply artificial neural networks to control double star smooth poles permanent magnet synchronous generator-PWM rectifiers set connected to standalone DC network. First, we present the model of the machine. Then a command based on a Multi-Layer Perceptron (MLP) neural network is applied to the control of the machine. Database generating method for neural network based on variations in machine parameters is also described in the document. The results show the performance of the neural network controller in robustness.


Auteur(s) : Gning Ndeye Seynabou; Nadia Ait Ahmed; Ndiaye Mouhamadou Falilou; Mourad Ait Ahmed; Thiaw Lamine; Benkhoris Mouhamed Fouad
Année de publication : 2019
Revue : 2019 IEEE 2nd International Conference on Renewable Energy and Power Engineering, REPE 2019
Type : Article
Mise en ligne par : NDIAYE Mouhamadou Falilou