Unmanned aerial vehicle flight control strategy design method using gust environment

Abstract

The invention discloses an unmanned aerial vehicle flight control strategy design method using a gust environment. The method comprises the following steps: establishing a flight dynamics model of an unmanned aerial vehicle in the gust environment; the roll angle of the unmanned aerial vehicle, the roll angle speed caused by the wind field gradient and the vertical wind speed change rate are selected as state quantities, iterative training is conducted on the state quantities through a reinforcement learning Q-learning algorithm, and an optimal control strategy is obtained; a flight control decision is made for the unmanned aerial vehicle in the gust environment according to the obtained optimal control strategy, and the real-time roll angle of the unmanned aerial vehicle is controlled through a PID controller to change the course of the unmanned aerial vehicle, so that the unmanned aerial vehicle finds up airflow and climbs by using the unmanned aerial vehicle; the method effectively overcomes the problems that a conventional common unmanned aerial vehicle flight control method using the gust environment needs a complicated debugging process and is not ideal in effect, can automatically adapt to different gust environments, and remarkably improves the all-weather safe flight capability of the unmanned aerial vehicle.

Description

technical field [0001] The invention relates to the technical field of UAV flight control methods, in particular to a UAV flight control strategy design method utilizing a gust environment. Background technique [0002] UAVs are playing an increasingly important role in various fields with their unique advantages. The tasks currently performed by UAVs usually require them to have better endurance performance. When UAVs fly in the air, especially when crossing mountains, seas and complex urban environments, they often encounter various severe atmospheric turbulence. When the turbulence has an upward velocity component, theoretically, UAVs can take advantage of This increases lift; and when encountering downward airflow, the UAV can reduce the lift. During this process, the average lift of the UAV is enough to offset the gravity and maintain its normal flight, which can effectively improve the UAV's lift. Endurance time and range. [0003] However, the current conventional ...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problems of difficult debugging and unsatisfactory results of conventional UAV flight control methods using gust environment, a design method of flight control strategy for UAV using gust environment based on reinforcement learning technology is proposed, which can automatically adapt to gust environment, significantly Improve the all-weather safe flight capability of drones

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