Sensor fault-tolerant control for a doubly fed induction generator in a smart grid

被引：4

作者：

Conchas, Robin F. ^{[1
]}

Sanchez, Edgar N. ^{[1
]}

Ricalde, Luis J. ^{[2
]}

Alvarez, Jesus G. ^{[3
]}

Alanis, Alma Y. ^{[3
]}

机构：

[1] CINVESTAV, Elect Engn Dept, Un Guadalajara, Ave Bosque 1145, Zapopan 45017, Jalisco, Mexico

[2] Univ Autonoma Yucatan, Fac Ingn, Ave Ind contaminantes,POB 115, Merida, Yucatan, Mexico

[3] Univ Guadalajara, Innovat Based Informat & Knowledge Dept, CUCEI, Marcelino Garcia Barragan 1421, Guadalajara 44430, Jalisco, Mexico

来源：

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2023年 / 117卷

关键词：

Fault-tolerant control; Artificial neural networks; Smart grids; Doubly fed induction generator; Power converters; SLIDING MODE CONTROL; WIND; POWER;

D O I：

10.1016/j.engappai.2022.105527

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This study proposes a sensor fault-tolerant controller for a doubly fed induction generator connected to a smart grid. Mathematical models are the main tools for the synthesis of modern control systems; however, an accurate model for complex systems is not always available. Therefore, in this study, a recurrent high-order neural network trained with an extended Kalman filter is proposed to develop a mathematical model for a wind turbine with a doubly fed induction generator connected to a smart grid. The neural model is combined with a modified discrete-time sliding mode controller, which compensates for the presence of sensor faults on each of the state variables on both sides of the back-to-back converter. Real-time results are included to illustrate the effectiveness of the proposed scheme under five sensor faults.

引用

页数：12

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