一种持续侦察无人机集群规模自适应调控方法

An Adaptive Scale Control Method of Multiple UAVs for Persistent Surveillance

无人机集群(unmanned aerial vehicles,UAVs)持续侦察是多无人机协同控制中一个重要的研究方向.随着任务环境和使命需求越来越复杂,对无人机集群可重构性和柔性的要求也越来越高.其中,对于自适应可重构无人机集群,无人机的规模数量是最基本的控制要素之一.然而,目前大部分无人机集群的研究都侧重于特定任务背景下的路径规划,而集群规模的动态调整则未被考虑.针对传统无人机集群侦察设计中,集群的数量难以自适应调整以匹配不同侦察环境、不同侦察态势的问题,提出了基于区域信息熵的"数字草皮"及其植物量变化模型,模仿草皮-食草动物生态系统中的动态平衡机制,设计了目标区域-无人机集群持续侦察体系中的规模控制方法.在此基础上,研究了侦察体系达到稳定时群落矩阵和平衡点的情况,探讨了在不同任务环境中、不同效能约束限制下,无人机集群规模的自适应调控方法,并利用仿真和可视化手段对平衡点的存在性和系统的收敛性进行了验证.

Unmanned aerial vehicles swarm persistent surveillance is an important application in the multiple unmanned aerial vehicles（UAVs）.With the increasing complexity of environment and tasks in surveillance mission,the requirement of UAV swarm reconfiguration and flexibility is also rising.To the adaptive and reconfigurable UAVs swarm,the amount of UAV is one of the basic control factors.However,most studies in UAV swarm control focus on control cooperative path planning in given mission,while dynamic deployment of the UAV amount in swarm system is neglected.In the surveillance design of traditional UAVs swarm,the amount of swarm is hard to adaptively adjust to match the different surveillance environments and various situations.To solve this kind of problem,a＂digital turf＂variation model is proposed on the base of the regional information entropy.Moreover,we imitate a dynamic balancing mechanism in the turf-herbivore ecosystem and design the scale control method in target region-UAV swarm.What＇s more,on this basis,we study the biomes matrix and equilibrium point situation when surveillance system reaches stable and discusses adaptive adjusting method of UAV swarm in different mission environments with different efficiency constraints.Finally,the existence of equilibrium point and the convergence of system are demonstrated by simulation.