Robust Control of Double Star PMSG using Artificial Neural Network

被引：0

作者：

Seynabou, Gning Ndeye ^{[1
,2
]}

Ahmed, Nadia Ait ^{[1
]}

Falilou, Ndiaye Mouhamadou ^{[3
]}

Ahmed, Mourad Ait ^{[1
]}

Lamine, Thiaw ^{[2
]}

Fouad, Benkhoris Mouhamed ^{[1
]}

机构：

[1] Univ Nantes, Genie Elect, Ireena, St Nazaire, France

[2] Univ Cheikh Anta Diop Dakar, Genie Elect, LER, Dakar, Senegal

[3] Univ Cheikh Anta Diop Dakar, Genie Elect, CIFRES, Dakar, Senegal

来源：

PROCEEDINGS OF 2019 IEEE 2ND INTERNATIONAL CONFERENCE ON RENEWABLE ENERGY AND POWER ENGINEERING (REPE 2019) | 2019年

关键词：

double star generator; neural network con- troller (NNC); dynamic modeling; standalone DC network; vari- ation parameters;

D O I：

10.1109/repe48501.2019.9025120

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

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 vari- ations in machine parameters is also described in the document. The results show the performance of the neural network controller in robustness.

引用

页码：248 / 253

页数：6

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