Autonomous guidance and control method of unmanned aerial vehicle based on ddpg

Abstract

The invention provides a DDPG-based autonomous guidance and control method for an unmanned aerial vehicle, which respectively establishes a three-degree-of-freedom motion model of the unmanned aerial vehicle, a maneuvering control model of the unmanned aerial vehicle, a three-dimensional model of a reference terrain and a three-dimensional model of a mountain peak; calculates the current position of the unmanned aerial vehicle The value of the degree of influence of terrain obstacles under the control system; build the evaluation network, the strategy network and the corresponding target network, and train the evaluation network and the strategy network; use the training result as the UAV flight control outer loop controller to control the two UAVs. Tilt angle to overload and drone speed. The invention combines the deep reinforcement learning method with the guidance and control of the unmanned aerial vehicle, conducts learning and training in an offline simulation environment, and then implements practical application after meeting the requirements, which greatly enhances the autonomy of the unmanned aerial vehicle in the process of performing tasks, and improves the the efficiency of the UAV's mission.

Description

technical field [0001] The invention relates to the field of flight maneuver control and artificial intelligence, in particular to an autonomous guidance control method of an unmanned aerial vehicle. Background technique [0002] In recent years, with the development of unmanned aerial vehicle technology, the performance of unmanned aerial vehicle has been improved rapidly. Whether it is military unmanned aerial vehicle or civil unmanned aerial vehicle, various new technologies emerge one after another. Among them, improving the autonomous flight ability of UAVs, reducing human intervention, and avoiding human errors are the research priorities of UAV researchers in various countries. The traditional UAV flight guidance control method usually realizes the UAV flight guidance by designing a trajectory tracking controller after obtaining the required flight track in the required task area. The controller mostly adopts PID control, linear two Methods such as subtype regulators...

AI Technical Summary

Problems solved by technology

However, when the environment changes greatly, none of the above-mentioned trajectory tracking controllers has the ability to independently solve emergencies. Only after the UAV operator manually intervenes, the UAV can continue to complete the task. Improve the efficiency of UAV missions

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