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Aeroservoelastic Pitch Control of Stall-Induced Flap/Lag Flutter of Wind Turbine Blade Section

机译:风力机叶片节失速襟翼/滞后颤振的气动弹性节距控制

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The aim of this paper is to analyze aeroelastic stability, especially flutter suppression for aeroelastic instability. Effects of aeroservoelastic pitch control for flutter suppression on wind turbine blade section subjected to combined flap and lag motions are rarely studied. The work is dedicated to solving destructive flapwise and edgewise instability of stall-induced flutter of wind turbine blade by aeroservoelastic pitch control. The aeroelastic governing equations combine a flap/lag structural model and an unsteady nonlinear aerodynamic model. The nonlinear resulting equations are linearized by small perturbation about the equilibrium point. The instability characteristics of stall-induced flap/lag flutter are investigated. Pitch actuator is described by a second-order model. The aeroservoelastic control is analyzed by three types of optimal PID controllers, two types of fuzzy PID controllers, and neural network PID controllers. The fuzzy controllers are developed based on Sugeno model and intuition method with good results achieved. A single neuron PID control strategy with improved Hebb learning algorithm and a radial basic function neural network PID algorithm are applied and performed well in the range of extreme wind speeds.
机译:本文的目的是分析气动弹性稳定性,尤其是对气动弹性不稳定性的颤振抑制。很少研究航空气动弹性桨距控制对受襟翼和滞后运动共同影响的风力涡轮机叶片截面的抑制作用。这项工作致力于通过气动弹性节距控制来解决风力涡轮机叶片失速引起的扑翼的襟翼和边缘不稳定性。气动弹性控制方程结合了襟翼/滞后结构模型和非稳态非线性气动模型。非线性结果方程通过围绕平衡点的小扰动线性化。研究了失速引起的襟翼/滞后颤振的不稳定性特征。螺距执行器由二阶模型描述。通过三种最优PID控制器,两种模糊PID控制器和神经网络PID控制器来分析航空弹性控制。基于Sugeno模型和直觉方法开发了模糊控制器,取得了良好的效果。应用了具有改进的Hebb学习算法和径向基函数神经网络PID算法的单神经元PID控制策略,并在极端风速范围内表现良好。

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