High Order Recurrent Neural Control for Wind Turbine with a Permanent Magnet Synchronous Generator

被引：0
|
作者：
Ricalde, Luis J. [1 ]
Cruz, Braulio J. [1 ]
Sanchez, Edgar N. [2 ]
机构：
[1] UADY, Fac Ingn, Av Ind Contaminantes Perifer Norte Apdo Post 115, Merida, Yucatan, Mexico
[2] CINVESTAV, Unidad Guadalajara, Guadalajara 45091, Jalisco, Mexico
来源：
COMPUTACION Y SISTEMAS | 2010年 / 14卷 / 02期
关键词：
Neural networks; Wind turbine; Permanent magnet synchronous generator; Maximum power control; Lyapunov methodology;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, an adaptive recurrent neural control scheme is applied to a wind turbine with permanent magnet synchronous generator. Due to the variable behavior of wind currents, the angular speed of the generator is required at a given value in order to extract the maximum available power. In order to develop this control structure, a high order recurrent neural network is used to model the turbine-generator model which is assumed as an unknown system; a learning law is obtained using the Lyapunov methodology. Then a control law, which stabilizes the reference tracking error dynamics, is developed using Control Lyapunov Functions. Via simulations, the control scheme is applied to maximum power operating point on a small wind turbine.
引用
收藏
页码：133 / 143
页数：11
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