This paper assesses the use of a ground-based wind measuring LiDAR (Light Detection and Ranging) for remote sensing of incoming wind gusts at the landing site of an autonomous quadrotor. The experimental verification results show that the scalar measurements from the LiDAR were able to recreate the horizontal wind vector even with wind direction variation. Comparisons were conducted against conventional cup anemometers with wind vanes, and these show a good correlation. Upwind LiDAR measurements were used to predict the downstream wind using a transport model. This prediction compared with the downwind measurement shows a good correlation. This wind preview information from the LiDAR is then incorporated into a disturbance feedforward control scheme to increase the gust resilience of the vehicle. Simulation and experimental results demonstrate the system's efficacy.

In order to operate safely in windy and gusty conditions, multirotor VTOL aircraft require gust resilience. This paper shows that their gust rejection properties can be improved by applying a small amount of fixed outward rotor tilt. Standard aerodynamic models of the rotors are incorporated into two dynamic models to assess the gust rejection properties. The first case is a conceptual birotor planar VTOL aircraft. The dependence of the trim and stability on the tilt angle are analyzed. The aircraft is stabilized using a pole-placement approach in order to obtain consistent closed-loop station-keeping performance in still air. The effect of gusts on the resulting response is determined by simulation. The second case study is for a quadrotor with a 10∘ outward rotor tilt. The aerodynamic coefficients are analyzed for trimmed station-keeping over a range of steady wind speeds. An LQR controller is used to apply station-keeping that includes integral action, and the gust responses are again obtained using simulation. The results show that the outward rotor tilt causes the aircraft to pitch down into a lateral gust, providing lateral force that opposes the gust and so significantly improving the gust rejection properties.

Autonomous outdoor operations of Unmanned Aerial Vehicles (UAVs), such as quadrotors, expose the aircraft to wind gusts causing a significant reduction in their position-holding performance. This vulnerability becomes more critical during the automated docking of these vehicles to outdoor charging stations. Utilising real-time wind preview information for the gust rejection control of UAVs has become more feasible due to the advancement of remote wind sensing technology such as LiDAR. This work proposes the use of a wind-preview-based Model Predictive Controller (MPC) to utilise remote wind measurements from a LiDAR for disturbance rejection. Here a ground-based LiDAR unit is used to predict the incoming wind disturbance at the takeoff and landing site of an autonomous quadrotor UAV. This preview information is then utilised by an MPC to provide the optimal compensation over the defined horizon. Simulations were conducted with LiDAR data gathered from field tests to verify the efficacy of the proposed system and to test the robustness of the wind-preview-based control. The results show a favourable improvement in the aircraft response to wind gusts with the addition of wind preview to the MPC; An 80% improvement in its position-holding performance combined with reduced rotational rates and peak rotational angles signifying a less aggressive approach to increased performance when compared with only feedback based MPC disturbance rejection. System robustness tests demonstrated a 1.75 s or 120% margin in the gust preview’s timing or strength respectively before adverse performance impact. The addition of wind-preview to an MPC has been shown to increase the gust rejection of UAVs over standard feedback-based MPC thus enabling their precision landing onto docking stations in the presence of wind gusts.