Exploration on the Stability of Unmanned Aerial Vehicles against Thermal Airflow Interference in Fire Scenes
Abstract
In view of the problems such as unstable attitude, hovering deviation, and reduced operational accuracy of fire-fighting drones caused by the superposition of multi-source disturbances such as high-temperature thermal plume and strong turbulence at the fire scene, this paper systematically reviews the relevant technologies for drones to resist thermal airflow interference. First, the causes of hot air flow at the fire scene were identified, and then the specific impact of hot air flow on the flight stability of the unmanned aerial vehicle was analyzed. Subsequently, key technologies such as disturbance perception, dynamic modeling, anti-interference control, and path planning were systematically sorted out, with a focus on comparing the practical application effects of mainstream algorithms such as PID control, robust control, and model predictive control in the complex environment of the fire scene. Finally, summarize the shortcomings of current research in terms of real-time disturbance perception accuracy and adaptability to extreme high-temperature environments, and look forward to future technological development directions. The study found that the combination of disturbance observation + feedforward compensation +PID/ robust control has the best anti-interference effect and can provide reliable theoretical support and technical guarantee for the stable operation of fire-fighting drones in extreme fire scenes.