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- W2354617939 abstract "Variable-pitch control is one of key technologies in variable-speed and constant-frequency(VSCF)wind turbine.Because of hysteretic nonlinear characteristics,variable-pitch system adopting traditional PID algorithm can't meet the requirements of control object.From the practical operation situation of 1 MW VSCF wind turbine,it can be seen that PID controller parameters need to be adjusted online all the time,so the neural network variable-speed control based on Hebbina supervised learning algorithm was proposed.Learning offline on the basis of the practical data of wind turbine operation gives the learning rate ηi of Hebbina supervised learning algorithm,and then adjusting online is performed in order to make the wind turbine stay in the best running situation.The simulated results of 1 MW wind turbine generator system adopting traditional PID were compared with those adopting Hebbina supervised learning algorithm.It can be seen that the dynamic and steady characteristics of the latter are obviously superior to those of the former.The present conclusions will play important roles in real operations." @default.
- W2354617939 created "2016-06-24" @default.
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- W2354617939 date "2007-01-01" @default.
- W2354617939 modified "2023-09-28" @default.
- W2354617939 title "Neural network variable-pitch control based on Hebbina supervised learning algorithm" @default.
- W2354617939 hasPublicationYear "2007" @default.
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