Onboard Wind-Preview Model Predictive Control Using Pitot-Static Sensing for Multirotor UAVs

2026-09-25

AI Summary

This study addresses the inherent control latency in existing UAV gust alleviation methods, which can only passively compensate for wind disturbances after their occurrence. To overcome this limitation, we propose a wind preview mechanism based on a low-cost pitot-static sensor that feeds forward upstream wind velocity predictions into a nonlinear model predictive control (NMPC) framework, enabling active disturbance rejection. Furthermore, the inertial trade-off effect introduced by the boom length is quantitatively analyzed. This approach facilitates a paradigm shift from passive response to proactive suppression. Outdoor flight experiments demonstrate that the proposed method reduces along-wind position errors by 54% compared to a baseline controller, significantly enhancing the hovering stability of UAVs in gusty environments.

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.

Problem

• wind gust rejection
• multirotor UAVs
• hovering stability
• reactive control
• wind disturbance

Innovation

• Wind-Preview
• Model Predictive Control
• Pitot-Static Sensing
• Gust Rejection
• Multirotor UAVs