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Evaluation of Sailing Flight Optimization Algorithm for the Dual Aircraft Platform Concept

机译:双飞机平台概念的帆船飞行优化算法评估

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Dual-aircraft platform (DAP) is a novel stratospheric satellite concept that features two tethered glider-like unmanned aerial systems which exploit wind speed differential across altitudes (i.e. vertical wind shear) to literally sail without propulsion, analogous to a kite-surfer. This paper describes a sailing flight optimization algorithm/strategy for refining the DAP sailing flight target requirements which accounts for uncertainties (error) in the precomputed (initial guess) target flight conditions. This autotuning strategy is a passive calculation method utilizing a performance index (PI) which consists of cost functions for control actuation and trajectory tracking to identify optimal flight requirements for sailing. The performance index is used in combination with autonomous angle sweeps in the roll, pitch, and yaw axes to determine a new sailing condition. Flight simulation results are presented for two scenarios involving uncertainties in the wind conditions and aircraft aerodynamics, respectively. The potential benefits and drawbacks of the strategy are discussed.
机译:双飞机平台(DAP)是一种新型的平流层卫星概念,具有两个束缚滑翔机类似的无人空中系统,它在没有推进的情况下,在真正的风速差分(即垂直风剪),没有推进,类似于风筝冲浪者。本文介绍了一种帆船航班优化算法/策略,用于精炼DAP帆船飞行目标要求,其考虑了预先计算(初始猜测)目标飞行条件的不确定性(错误)。这种自动训练策略是利用性能指数(PI)的被动计算方法,该方法包括用于控制驱动和轨迹跟踪的成本函数,以确定帆船的最佳飞行要求。性能指数与卷,俯仰和偏航轴中的自主角度扫描结合使用,以确定新的帆船状况。飞行模拟结果分别涉及风能和飞机空气动力学在风力条件和飞机空气动力学的不确定性的情况下。讨论了该策略的潜在利益和缺点。

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