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状态空间空气动力模型揭示了扑翼飞行中的高力控制能力和可预测性。

State-space aerodynamic model reveals high force control authority and predictability in flapping flight.

机构信息

Mechanical Engineering Department, The Pennsylvania State University, University Park, PA 16801, USA.

出版信息

J R Soc Interface. 2021 Aug;18(181):20210222. doi: 10.1098/rsif.2021.0222. Epub 2021 Aug 4.

Abstract

Flying animals resort to fast, large-degree-of-freedom motion of flapping wings, a key feature that distinguishes them from rotary or fixed-winged robotic fliers with limited motion of aerodynamic surfaces. However, flapping-wing aerodynamics are characterized by highly unsteady and three-dimensional flows difficult to model or control, and accurate aerodynamic force predictions often rely on expensive computational or experimental methods. Here, we developed a computationally efficient and data-driven state-space model to dynamically map wing kinematics to aerodynamic forces/moments. This model was trained and tested with a total of 548 different flapping-wing motions and surpassed the accuracy and generality of the existing quasi-steady models. This model used 12 states to capture the unsteady and nonlinear fluid effects pertinent to force generation without explicit information of fluid flows. We also provided a comprehensive assessment of the control authority of key wing kinematic variables and found that instantaneous aerodynamic forces/moments were largely predictable by the wing motion history within a half-stroke cycle. Furthermore, the angle of attack, normal acceleration and pitching motion had the strongest effects on the aerodynamic force/moment generation. Our results show that flapping flight inherently offers high force control authority and predictability, which can be key to developing agile and stable aerial fliers.

摘要

会飞的动物采用快速、大幅度自由度的翅膀拍打运动,这是它们与旋转或固定翼机器人飞行器的关键区别,后者的空气动力面运动有限。然而,扑翼空气动力学的特点是极不稳定的三维流,难以建模或控制,准确的空气动力预测通常依赖于昂贵的计算或实验方法。在这里,我们开发了一种计算效率高且基于数据驱动的状态空间模型,用于将翅膀运动动态映射到空气动力上。该模型使用了总共 548 种不同的扑翼运动进行训练和测试,其准确性和通用性超过了现有的准稳态模型。该模型使用 12 个状态来捕捉与力产生相关的非定常和非线性流体效应,而无需显式的流体流动信息。我们还对关键翅膀运动变量的控制能力进行了全面评估,发现半拍周期内的翅膀运动历史可以很大程度上预测瞬时空气动力。此外,攻角、法向加速度和俯仰运动对空气动力的产生有最强的影响。我们的结果表明,扑翼飞行具有固有高的力控制能力和可预测性,这可能是开发敏捷稳定的空中飞行器的关键。

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