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  • 标题:RBF NEURAL NETWORK ROBUST ADAPTIVE CONTROL FOR WIND GENERATOR SYSTEM
  • 本地全文:下载
  • 作者:Zuo ; Y. Wang ; Y. N. Zhang
  • 期刊名称:Mechanika
  • 印刷版ISSN:1392-1207
  • 出版年度:2011
  • 卷号:17
  • 期号:5
  • 页码:557-561
  • DOI:10.5755/j01.mech.17.5.736
  • 语种:English
  • 出版社:Kauno Technologijos Universitetas
  • 摘要:Among the main research subjects in the windturbine domain, the control of wind generator system isconsidered an interesting application area for control the-ory and engineering. The control strategies must cope withthe exacting characteristics presented by WECS such asthe nonlinear behavior of the system, the random variabil-ity of the wind and external perturbations. Djohra et al. [1]model and simulate a wind turbine and an induction gen-erator system as an electricity source in the southern partsof Algeria, and the obtained results have then been vali-dated by the HOMER software confirming the effective-ness of the developed program. Jordi et al. [2] analyze andcompares different control tuning strategies for a variablespeed wind energy conversion system based on a perma-nent-magnet synchronous generator (PMSG), and theaerodynamics of the wind turbine and a PMSG have beenmodeled. Valenciaga et al. [3] presents the control of avariable-speed wind energy conversion system based on abrushless doubly fed reluctance machine, and the controldesign is approached using multiinput second-order slidingtechniques. However, above-all papers have not consideredthe intelligent robust adaptive control method.
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