基于信息一致性的无人机紧密编队集结控制

提出了基于信息一致性的分段式无人机紧密编队集结控制策略,将集结过程分为3步:参考集结点选取和目标集结点分配、形成松散编队以及形成紧密编队。首先,以线切入预定航线的方式计算参考集结点,按照松散编队队形展开生成目标集结点,并利用基于三维距离空间的优化选择算法,将目标集结点快速、准确地分配给每架无人机。然后,使用速度一致性实现向目标集结点定点集结和向松散编队伴航集结,通过非精确的航迹控制快速形成松散编队,提高编队集结的效率。接下来,启动速度、姿态一致性来实现编队最终的精确航迹控制,并逐步压缩编队队形进入紧密编队,避免发生碰撞,完成从松散编队到紧密编队的平稳过渡,同时准确地跟踪预定航线。使用协同修正方法抑制了测量误差、协同误差和通信延迟,提高了紧密编队的稳定性和控制精度。最后,基于MATLAB平台环境对所提三维集结控制策略进行了仿真,验证了其合理性与有效性。

Swarm control of UAV close formation based on information consensus

Sectional swarm control strategy of close unmanned aerial vehicle (UAV) formation is proposed based on information consensus. Swarm process is decomposed of three steps, including choosing reference rendezvous and allocating target rendezvous, as well as generating loose formation and generating close formation. Firstly, reference rendezvous are computed out as UAVs enter the predefined flight path along straight line and target rendezvous form as loose formation spreads out. Using optimization selection algorithm in the three-dimensional distance space, target rendezvous are assigned to each UAV quickly and accurately. Then, velocity consensus is applied to achieving stable point swarm towards target rendezvous and partner swarm towards loose formation. Swarm efficiency of the formation is improved with imprecise track control. Thirdly, close formation is formed ultimately with velocity and attitude consensus for precise track control, where transient process is smooth with gradual compression of geometrical configuration to avoid collision. Measurement errors, collaborative errors and communication delays are depressed by the synchronization method that the stability and the control accuracy of the close formation are improved. Finally, reasonableness and efficiency of the suggested three-dimensional formation swarm strategy are verified by MATLAB experiment.