Reinforcement learning based air combat maneuver decision making method of unmanned aerial vehicle (UAV)

Abstract

The invention provides a reinforcement learning based air combat maneuver decision making method of a UAV. A motion model of an airplane platform is created; principle factors that influence the air combat situation are analyzed; on the basis of the motion model and analysis on the air combat situation factors, a dynamic fuzzy Q learning model of air combat maneuver decision making is designed, and essential factors and an algorithm flow of reinforcement learning are determined; a state space of air combat maneuver decision making is fuzzified and serves as state input of reinforcement learning; typical air combat motions are selected as basic motions of reinforcement learning, and the triggering intensities of fuzzy rules are summed in a weighted manner, and a continuous motion space is covered; and on the basis of an established air combat dominant function, a return value of reinforcement learning is set in a rewards and punishment values weighing-superposing method. Thus, the autonomous maneuver decision making capability of the UAV during air combat can be improved effectively, the robustness is higher, an autonomous searching optimization performance is higher, and decisionsmade by the UAV are improved continuously in continuous simulation and learning.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence, and in particular relates to an implementation method for air combat maneuver decision-making of unmanned aircraft. Background technique [0002] At present, drones have been able to complete tasks such as reconnaissance, surveillance and ground attack, and are playing an increasingly irreplaceable role in modern warfare. However, due to the higher real-time requirements for air combat, the current ground station remote control method for UAVs is difficult to achieve accurate and timely control of UAVs in order to gain an advantage in air combat. Therefore, improving the intelligence level of UAVs and enabling UAVs to automatically generate control commands to complete maneuvers in air combat according to the situational environment is the current main research direction. [0003] The essence of allowing UAVs to complete autonomous decision-making in air combat maneuvers is to co...

AI Technical Summary

Problems solved by technology

Since the situation of air combat is more complex than other tasks, it is difficult to fully cover the situation space of air com

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