固定翼无人机集群预定时间仿射编队机动控制
收稿日期: 2025-01-20
修回日期: 2025-02-27
录用日期: 2025-03-17
网络出版日期: 2025-03-28
基金资助
国家自然科学基金(U20B2001);航空科学基金(2024Z023077001)
Predefined-time affine formation maneuvering control for fixed-wing UAV swarm
Received date: 2025-01-20
Revised date: 2025-02-27
Accepted date: 2025-03-17
Online published: 2025-03-28
Supported by
National Natural Science Foundation of China(U20B2001);Aeronautical Science Foundation of China(2024Z023077001)
针对传统“领航-跟随”仿射编队机动控制方法收敛时间难以预先设定的问题，提出一种适用于固定翼无人机（UAV）集群的预定时间仿射编队机动控制方法。首先，设计了适用于有向通信拓扑的预定时间仿射观测器，确保跟随者无人机能够在预定收敛时间内精确观测期望的仿射编队机动状态。其次，针对输入约束下的无人机状态跟踪问题，将其转化为时变控制系数问题，并采用反步法设计了基于 Nussbaum 函数的状态跟踪控制器加以解决。此外，针对无人机飞行过程中的未知扰动，构建了预定时间扰动估计器实现主动补偿。通过李雅普诺夫稳定性理论和预定时间理论，严格证明了系统的稳定性和预定时间收敛性。最后，通过仿真验证表明，该方法能够在预定时间内实现固定翼无人机集群的仿射编队机动控制，并具备抗干扰和抗饱和性能。同时，对比仿真结果进一步验证了所提方法的优越性。
严超 , 张泽旭 , 崔祜涛 , 张凯 , 刘京宗 . 固定翼无人机集群预定时间仿射编队机动控制[J]. 航空学报, 2025 , 46(22) : 331824 -331824 . DOI: 10.7527/S1000-6893.2024.31824
To address the problem of predefining the convergence time in traditional “leader-follower” affine formation maneuvering control methods， a predefined-time affine formation maneuvering control method for fixed-wing Unmanned Aerial Vehicle （UAV） swarm is proposed. First， a predefined-time affine observer is designed for directed communication topology to ensure that the follower UAVs can accurately observe the desired affine formation maneuvering states within the specified time. Next， the UAV state tracking problem under input constraints is transformed into a time-varying control coefficient problem， which is solved using a backstepping-based state tracking controller incorporating the Nussbaum function. Additionally， a predefined-time disturbance estimator is constructed to actively compensate for unknown disturbances during flight. The system’s stability and predefined-time convergence are rigorously proven using Lyapunov stability theory and predefined-time theory. Finally， simulation results demonstrate that the proposed method can achieve affine formation maneuvering control for fixed-wing UAV swarm within the predefined time， while exhibiting disturbance rejection and anti-saturation performance. Furthermore， the comparative simulation results provide additional validation of the superiority of the proposed method.
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