Zhou Huan, Li Yintong, Han Tong
Aviation Engineering School, Air Force Engineering University, Xi'an, China.
Comput Intell Neurosci. 2022 Aug 11;2022:6398039. doi: 10.1155/2022/6398039. eCollection 2022.
UAV swarm anticollision system is very important to improve the flight safety of the whole swarm formation, while the existing system design methods are still insufficient in realizing autonomous and cooperative anticollision. Based on the cognitive game theory, an intelligent decision-making and control method for UAV swarm anticollision is designed. Firstly, by using the idea of swarm intelligence, basic flight behaviors of UAV swarm are defined as five basic flight rules, such as cohesion, following, self-guidance, dispersion, and alliance. Further, the cognitive security domain of UAV swarm is constructed by setting the overall anticollision rules of the swarm and the anticollision rules of individual members. On this basis, the anticollision problem of UAV swarm is transformed into a game problem involving two parties, and the solution method of decision and control strategy set is proposed. Finally, the stability of anticollision decision and control method is proved through eigenvalue theory. The simulation results show that the method proposed in this paper can effectively realize the autonomous cooperative anticollision of UAV swarm and also has good algorithm real-time solution ability while ensuring flight safety.
无人机群防撞系统对于提高整个机群编队的飞行安全性非常重要,而现有的系统设计方法在实现自主协同防撞方面仍存在不足。基于认知博弈理论,设计了一种无人机群防撞的智能决策与控制方法。首先,利用群体智能的思想,将无人机群的基本飞行行为定义为凝聚、跟随、自引导、分散和结盟等五条基本飞行规则。进一步地,通过设定机群的整体防撞规则和个体成员的防撞规则,构建了无人机群的认知安全域。在此基础上,将无人机群的防撞问题转化为一个双方博弈问题,并提出了决策与控制策略集的求解方法。最后,通过特征值理论证明了防撞决策与控制方法的稳定性。仿真结果表明,本文提出的方法能够有效实现无人机群的自主协同防撞,在确保飞行安全的同时还具有良好的算法实时求解能力。