Fuzzy neural network output maximization control for sensorless wind energy conversion system

被引：60
|
作者：
Lin, Whei-Min [1 ]
Hong, Chih-Ming [1 ]
Cheng, Fu-Sheng [2 ]
机构：
[1] Natl Sun Yat Sen Univ, Dept Elect Engn, Kaohsiung 80424, Taiwan
[2] Cheng Shiu Univ, Dept Elect Engn, Kaohsiung, Taiwan
来源：
ENERGY | 2010年 / 35卷 / 02期
关键词：
Sliding mode speed observer; Fuzzy neural network (FNN); Wind turbine (WT); Induction generator (IG);
D O I：
10.1016/j.energy.2009.10.030
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
This paper presents the design of an online training fuzzy neural network (FNN) controller with a high-performance speed observer for the induction generator (IG). The proposed output maximization control is achieved without mechanical sensors such as the wind speed or position sensor, and the new control system will deliver maximum electric power with light weight, high efficiency, and high reliability. The estimation of the rotor speed is designed on the basis of the sliding mode control theory. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码：592 / 601
页数：10
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