联盟
控制重构
计算机科学
趋同(经济学)
理论(学习稳定性)
领域(数学)
算法
控制(管理)
人工智能
数学
法学
经济
嵌入式系统
机器学习
政治学
纯数学
经济增长
作者
Jiang Yan,Tingting Bai,Yin Wang
出处
期刊:Drones
[MDPI AG]
日期:2022-12-19
卷期号:6 (12): 431-431
被引量:6
标识
DOI:10.3390/drones6120431
摘要
Among the key technologies of Multi-Unmanned Aerial Vehicle (UAV) leader–follower formation control, formation reconfiguration technology is an important element to ensure that multiple UAVs can successfully complete their missions in a complex operating environment. This paper investigates the problem of formation reconfiguration due to battlefield mission requirements. Firstly, in response to the mission requirements, the article proposes the Ant Colony Pheromone Partitioning Algorithm to subgroup the formation. Secondly, the paper establishes the alliance for the obtained subgroups. For the problem of no leader within the alliance formed after grouping or reconfiguring, the Information Concentration Competition Mechanism is introduced to flexibly select information leaders. For the problem of the stability of alliance structure problem, the control law of the Improved Artificial Potential Field method is designed, which can effectively form a stable formation to avoid collision of UAVs in the alliance. Thirdly, the Lyapunov approach is employed for convergence analysis. Finally, the simulation results of multi-UAV formation control show that the partitioning algorithm and the competition mechanism proposed can form a stable alliance as well as deal with the no-leader in it, and the improved artificial potential field designed can effectively avoid collision of the alliance and also prove the highly efficient performance of the algorithm in this paper.
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