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

机译:风力涡轮机叶片段失速诱导襟翼/滞后的空气弹性沥青

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摘要

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:本文的目的是分析空气弹性稳定性,特别是气弹性不稳定的颤动抑制。很少研究了对经受组合翼片和滞后运动的风力涡轮机段扑振抑制的影响。该工作致力于通过Aeroservoelastic俯仰对照控制风力涡轮机叶片的失速凸起的破坏性浮动和边缘不稳定性。空气弹性控制方程组合了翼片/滞后结构模型和不稳定的非线性空气动力学模型。通过关于平衡点的小扰动线性化的非线性得到的等式。研究了失速诱导的襟翼/滞后颤动的不稳定性特性。间距执行器由二阶模型描述。通过三种类型的最佳PID控制器,两种类型的模糊PID控制器和神经网络PID控制器分析了Aeroservoelastic控制。模糊控制器是基于Sugeno模型和直觉方法而实现的,实现了良好的效果。应用具有改进的HEBB学习算法的单个神经元PID控制策略和辐射基本功能神经网络PID算法,并在极端风速范围内进行良好。

著录项

  • 作者

    Tingrui Liu;

  • 作者单位
  • 年度 2015
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
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