Cooperative Control of Multi-UAV for Multi-Targets Encirclement and Tracking Based on Potential Game

This paper investigates a cooperative control of multiple unmanned aerial vehicle (multi-UAV) for multiple target (multi-target) encirclement and tracking. Different from the existing works, target clustering and task assignment are considered in this paper. Target clustering according to Density Based Spatial Clustering of Applications with Noise (DBSCAN). The noise points are added as a new cluster or joining an adjacent cluster. When the distance between two clusters is relatively close, they are classified into a cluster group, which avoids wasting UAV resources. The potential game task allocation algorithm enables the UAVs to reach Nash equilibria and obtain the optimal allocation strategy in fast iterations. The encirclement and tracking guidance law is a coupled control method, which can make the UAV formation converge quickly and maintain stability. Finally, the effectiveness of the control strategy is verified by simulation.