Real-Time Data-Driven Adaptive Lift Regulation in Developing Long-Duration Gusts
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Portella-Delgado, Jhon Manuel, John T. Hrynuk, Meilin Yu, and Ankit Goel. “Real-Time Data-Driven Adaptive Lift Regulation in Developing Long-Duration Gusts.” Journal of Guidance, Control, and Dynamics, August 10, 2025. https://doi.org/10.2514/1.G008433.
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This is a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
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Abstract
UNCREWED aerial vehicles (UAVs) often operate in unstruc-tured, uncertain, and unsteady flow environments, leading tocomplex fluid–structure interactions. These interactions involvetime-varying flowfields around the physical structure, applying highly unsteady loads on the vehicle. In addition to stabilizingand regulating the vehicle dynamics, the flight control system thusmust also compensate for the unmeasured loads created by theseundesirable fluid–structure interactions. The most common mecha-nism by which the unstructured, uncertain, and unsteady nature manifests in the flow environment is gust [1,2]. The harsh flow conditions resulting from gusts negatively affect the performance of UAVs and severely restrict their operating envelopes. To overcomethe negative influence imposed by gust–vehicle interactions, active and passive flow control techniques, based on in situ flow condi-tions, need to be developed. However, designing such a controlsystem for effective gust mitigation is a challenging problem due tothe highly transient, high-dimensional, and nonlinear flow physicsof the gust–vehicle interactions.