文章基本信息

标题：Neural Sliding Mode Control of a DFIG Based Wind Turbine with Measurement Delay
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作者：Larbi Djilali ; H. Caballero-Barragán ; L.P. Osuna-Ibarra 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：13
页码：456-461
DOI：10.1016/j.ifacol.2018.07.320
语种：English
出版社：Elsevier
摘要：AbstractIn this paper, a robust predictor neural sliding mode control algorithm for a Doubly Fed Induction Generator based Wind Turbine is proposed. To improve the robustness of the proposed controller in presence of the parameter variations and disturbances, a Recurrent High Order Neural Network identifier trained on-line using an Extended Kalman Filter is proposed. In addition, to compensate the measurement delay in stator and rotor current, a robust predictor-based controller is integrated with the control scheme. To show the importance of the proposed control scheme, different experiments are done such as ideal condition, measurements delay, and presence of parameter variations. Simulation results illustrate the effectiveness of proposed control scheme even in presence of reference changing, parameter variations, and measurement delay. In addition, the stability, decoupling, and convergence are achieved.
关键词：KeywordsWind TurbineDouble Fed Induction GeneratorNeural NetworkExtended Kalman FilterSliding ModeTime-delayPredictive-Control