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Neural-Fly proposes online adaptive control method for quadrotors in strong winds

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Neural-Fly proposes a residual aerodynamic force adaptation law that combines wind-invariant representations with online least squares, for online adaptive control of quadrotor UAVs under strong winds. The method trains a network using public flight data and conducts comparative experiments on figure-8 trajectory tracking in a PyBullet quadrotor and a steady wind field, demonstrating the fast adaptation capability brought by domain-shift separation. The above results come from simulation experiments; real flight validation has not yet been seen.

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  1. Neural-Fly: Online Adaptive Control for Quadrotors in Strong Winds

    Neural-Fly proposes a residual aerodynamic force adaptation law that combines wind-invariant representations with online least squares for online adaptive control of quadrotors in strong winds. The method trains a network on public flight data and conducts comparative figure-8 trajectory tracking experiments with a PyBullet quadrotor in a steady wind field, demonstrating rapid adaptation enabled by domain-shift separation.

    Guyuehome ·

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Motion controlData and simulationResearch papers

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