Title :
Sliding mode variable pitch control of wind turbine via fuzzy neural network
Author :
Qingsong, Liu ; Suxiang, Qian
Author_Institution :
Jiaxing Univ., Jiaxing, China
Abstract :
According to variable pitch wind characteristic and control requirements, and from the view of enhancing control system robustness, a fuzzy neural network sliding model control strategy is proposed for variable pitch control. Wind turbine model is established by fuzzy neural network and composed closed-loop control system, adaptive sliding mode controller based fuzzy neural network to reduce influence of wind varying. The results show that the proposed combined control tactics are easy to implement, and the combined control system of wind power system has good robustness and fast dynamic response, which verifies the accuracy and feasibility of the combined control tactics.
Keywords :
adaptive control; closed loop systems; fuzzy control; neurocontrollers; power generation control; robust control; variable structure systems; wind turbines; adaptive sliding mode controller; closed-loop control system; control system robustness; fuzzy neural network sliding model control strategy; sliding mode variable pitch control; variable pitch wind characteristic; wind power system; wind turbine; Adaptation models; Control systems; Fuzzy control; Fuzzy neural networks; Niobium; Wind power generation; Wind turbines; fuzzy control; neural network; sliding mode control; variable pitch wind turbine; wind power generation;
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
Print_ISBN :
978-1-4673-2581-3