Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control
Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control作者机构：Faculty of Science and Engineering School of Civil and MechanicalEngineering Curtin University Perth Australia
出 版 物：《Frontiers of Mechanical Engineering》 (机械工程前沿（英文版）)
年 卷 期：2017年第12卷第3期
页 面：377-388页
核心收录：
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 080801[工学-电机与电器] 0808[工学-电气工程] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：wind turbine nonlinear model maximum power tracking passive fault tolerant control adaptive neural control
摘 要：Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method.
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