仿狼群狩猎空间交互机制的无人机集群合围控制

The containment control of unmanned aerial vehicle (UAV) swarms with limited perception ranges is different from the traditional swarm control problem since the communication topology cannot ensure global connectivity all the time due to limited sensing. Although algorithms based on artificial potentials provide possible solutions by introducing attractions and repulsion to maintain the swarm consensus, the regular requirement of perfect target-sensing for all UAV nodes is not feasible in most cases. Specifically, in some mission environments, signal interferences may cause the loss of node detection, and the losers may need the help of adjacent nodes to maintain formation stability, thus leading to spontaneous heterogeneous clusters specified by the functionalities of UAVs. Wolves are typical opportunistic predators that hunt prey by group coordination, whereas the spatial layout and interactive behavioral patterns are specific characteristics in the wolf-pack hunting processes. First, based on the analysis of empirical data, we propose a hierarchical wolf-pack interactive dynamics model, which employs the spatial probability distribution to modulate the strengths of the interactive potentials. Furthermore, we propose a heterogeneous enclosing control law for UAV swarms, which combines interactive dynamics with a hierarchical target observer. Through the hierarchical layout and adaption of interaction strengths, the interaction effects between weak and reliable nodes can be enhanced, which, in turn, improves system robustness under restricted perception abilities. Simulation results show the advantages of the proposed method on the control stability and relaxed demand for airborne sensing with perception limitations and fitness to harsh mission environments.