Multirotor drones improve hover using forward wind sensing and predictive control
Onboard Wind-Preview Model Predictive Control Using Pitot-Static Sensing for Multirotor UAVs
Robotics
Summary
Drones that hover outside struggle to stay steady when the wind gusts because the wind push is felt only after it starts moving the drone. The authors use a small sensor mounted ahead of the drone to measure wind before it hits, giving an early warning. This early wind information is fed into a smart control system that plans the drone’s movements to counteract the wind before it causes instability. Tests show this approach makes drones stay steadier, reducing position errors by over half compared to controls without forward wind sensing.
What this means in practice
- •For drone operators: Improve drone hovering performance outdoors by using onboard forward wind sensing and predictive control to anticipate and counteract wind gusts.
- •For small uav manufacturers: Design drones with a forward-mounted pitot-static sensor and predictive wind compensation to enhance stability in windy conditions.$Commercial implications: Enables sales of more stable drones for outdoors by integrating advanced wind-aware control systems that outperform current reactive methods.
Authors
Bas Meere, Eline Wisse, Laurens Vousten, Sander Doodeman, Elena Torta, Paula Chanfreut, Duarte Antunes
Abstract
Effective wind gust rejection and stable hovering are critical for the outdoor operation of autonomous drones. However, existing gust rejection methods are primarily reactive, inferring the disturbance from the resulting motion or measuring it at the airframe. Either way, the wind has already begun to act before it can be compensated. In this work, we anticipate the gust instead by measuring the wind ahead of the drone with a low-cost, low-weight pitot-static sensor mounted on a boom. The resulting wind preview is incorporated into a nonlinear model predictive controller (MPC), which optimizes the drone motion while anticipating wind disturbances. A longer boom offers more preview time but adds inertia and degrades flight performance. We characterize this trade-off in simulation and show that the optimal preview distance is not a fixed property of the platform, but shifts with the wind speed and with how quickly the drone can respond. Indoor hardware experiments confirm the trend and show that the proposed controller substantially improves hover performance against a PX4 baseline and an otherwise identical wind-unaware MPC. Outdoor experiments show that the error along the wind direction is reduced by 54 percent with respect to the baseline, demonstrating that a single wind-aligned sensor can significantly improve hovering performance.