A neural network replaces sensor-based residual computation in INDI controllers for quadrotors, enabling equivalent trajectory tracking performance without rotor RPM measurements, demonstrated experimentally with and without slung payloads.
Differential Flatness of Quadrotor Dynamics Subject to Rotor Drag for Accurate Tracking of High-Speed Trajectories
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abstract
In this paper, we prove that the dynamical model of a quadrotor subject to linear rotor drag effects is differentially flat in its position and heading. We use this property to compute feed-forward control terms directly from a reference trajectory to be tracked. The obtained feed-forward terms are then used in a cascaded, nonlinear feedback control law that enables accurate agile flight with quadrotors. Compared to state-of-the-art control methods, which treat the rotor drag as an unknown disturbance, our method reduces the trajectory tracking error significantly. Finally, we present a method based on a gradient-free optimization to identify the rotor drag coefficients, which are required to compute the feed-forward control terms. The new theoretical results are thoroughly validated trough extensive comparative experiments.
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cs.RO 1years
2025 1verdicts
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Learned Incremental Nonlinear Dynamic Inversion for Quadrotors with and without Slung Payloads
A neural network replaces sensor-based residual computation in INDI controllers for quadrotors, enabling equivalent trajectory tracking performance without rotor RPM measurements, demonstrated experimentally with and without slung payloads.