一种隧道贯通风场下无人机抗扰动飞行控制方法
By constructing a nonlinear dynamic model under the wind field of tunnel penetration and using multi-source data fusion technology, combined with a disturbance predictor based on a fluid dynamics model, stable and accurate flight of UAVs under strong wind disturbance conditions was achieved. This solved the problems of model complexity and response lag in traditional methods, and improved control accuracy and safety.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUAZHONG UNIV OF SCI & TECH
- Filing Date
- 2026-03-27
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies struggle to achieve stable, accurate, and safe flight of drones under tunnel ventilation conditions, especially in environments with strong wind disturbances. Traditional methods suffer from problems such as complex models, high computational load, response lag, and significant chattering.
A nonlinear dynamic model of a UAV under tunnel wind field is constructed. Multi-source data fusion is performed by combining ultra-wideband wireless communication, lidar and visual sensors. The position and attitude information of the UAV is output by using an extended Kalman filter. A disturbance predictor based on the tunnel fluid dynamics model is introduced. The desired attitude command and control torque are generated by inner and outer loop controllers to achieve feedforward compensation.
It significantly improves the anti-disturbance capability of UAVs in strong through-flow and turbulent environments, ensures the rapid response and robustness of the system, avoids the risk of collision or loss of control, and achieves high-precision flight control.
Smart Images
Figure CN122411481A_ABST