Analysis of a RBF Neural Network Based Controller for Pitch Angle of Variable-Speed Wind Turbines. (2017)

• Record Type: Journal Article
• Authors: Mjabber, El Kabira El; Hajjaji, Abdellah El; Khamlichi, Abdellatif
• Is Part Of: Procedia engineering. Volume 181(2017)
• Page Start: 552
• Page End: 559
• Publication Date: 2017
• Subjects: Variable-speed wind turbines -- Pitch angle control -- RBF neural network controller; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Conference proceedings; Periodicals; 620.005
• DOI: 10.1016/j.proeng.2017.02.433
• Languages: English
• ISSNs: 1877-7058

Abstract

Abstract: In order to control the pitch angle of blades in wind turbines in the rated power zone, an artificial neural network based controller is investigated in this work. The particular form of these controllers called Radial Basis Functions for network adaptation (RBF-NN) is considered. The wind turbine under the action of this controller was modeled as a first degree of freedom system by using Matlab/Simulink. Then, performance of the controller was analyzed numerically. The proposed controller was found to effectively improve the control performance against large uncertainties affecting the wind turbine system. Comparison with standard proportional integral controller was performed and the obtained results have demonstrated the relevance of the RBF-NN based controller.