A Lyapunov based switching control to track maximum power point of WECS

Mohammad Abu Jami'In, Takayuki Furuzuki, Eko Julianto

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

The control system is a key technology to extract maximum energy from the incident wind. By regulating aerodynamic control, it is possible to adapt the changes in wind speed by controlling shaft speed. Thus, the turbine generator can track maximum power extracted from wind. In this paper, we propose a Lyapunov based switching control under quasi-linear ARX neural network (QARXNN) model to track maximum power of wind energy conversion system. The switching index is used to measure the stability of nonlinear controller and selects linear or nonlinear controller in order to ensure the stability. Interestingly, a simple switching law can be built utilizing the parameters of model directly. Finally, we have compared the proposed algorithm of switching controller with another algorithm. The results show that the proposed algorithm has better control performance.

本文言語English
ホスト出版物のタイトル2016 International Joint Conference on Neural Networks, IJCNN 2016
出版社Institute of Electrical and Electronics Engineers Inc.
ページ3883-3888
ページ数6
2016-October
ISBN(電子版)9781509006199
DOI
出版ステータスPublished - 2016 10 31
イベント2016 International Joint Conference on Neural Networks, IJCNN 2016 - Vancouver, Canada
継続期間: 2016 7 242016 7 29

Other

Other2016 International Joint Conference on Neural Networks, IJCNN 2016
国/地域Canada
CityVancouver
Period16/7/2416/7/29

ASJC Scopus subject areas

  • ソフトウェア
  • 人工知能

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