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Online Control Design for Learn-to-Fly

机译:学习型飞行的在线控制设计

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摘要

Two methods were developed for online control design as part of a flight test effort to examine the feasibility of the NASA Learn-to-Fly concept. The methods use an aerodynamic model of the aircraft that is being identified in real-time onboard the aircraft to adjust the control parameters. One method employs adaptive nonlinear dynamic inversion, whereas the other consists of a classical autopilot structure. Effects from the interaction between the real-time modeling and the developed control laws are discussed. The Learn-to-Fly concept has been deemed feasible based on successful flights of both a stable and unstable aircraft.
机译:作为飞行测试工作的一部分,开发了两种方法用于在线控制设计,以检验NASA学会飞行概念的可行性。该方法使用在飞机上实时识别的飞机的空气动力学模型来调节控制参数。一种方法采用自适应非线性动态反演,而另一种方法则采用经典的自动驾驶仪结构。讨论了实时建模与已开发的控制律之间的相互作用所产生的影响。基于稳定和不稳定飞机的成功飞行,“学习飞行”概念被认为是可行的。

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