Hybrid Control of a Wind Induction Generator Based on Grey-Elman Neural Network

作者：Lin, Whei Min^*; Hong, Chih Ming; Huang, Cong Hui; Ou, Ting Chia

来源：IEEE Transactions on Control Systems Technology, 2013, 21(6): 2367-2373.

DOI：10.1109/TCST.2012.2231865

• Grey predictor
• improved Elman neural network (ENN)
• maximum power point tracking
• sliding-mode speed observer
• wind turbine generator

This brief presents the design of an optimal wind energy control system for maximum power point tracking. With the help of a grey predictor for the preprocessor, a high-performance online training Elman neural network (ENN) is designed to derive the turbine speed needed to extract maximum power from wind. Moreover, the connective weights of the improved ENN are trained online by the backpropagation learning algorithm. Compared to earlier methods, better results are obtained when the ENN controller is used together with the grey system modeling approach. Performance of the proposed approach is verified by the experimental results.

• 出版日期2013-11
• 单位中山大学