We present an overview of formation control for multi-agent systems. Multi-agent formation cooperation is important to accomplish assigned tasks more efficiently and safely compared to a single agent. For the way information flows between agents, we divide the available results into communication-based topologies as well as vision-based formation controls. Then, we summarize the problem formulation, discuss the differences, and review the latest results on formation control schemes. Lastly, we give research recommendations for multi-intelligent agent controls in a certain period in the future.

The problem of vision-based fixed-wing UAV formation control under communication limitations and the presence of measurement errors was investigated. In the first part of this paper, the single UAV motion model and the process of estimating the neighboring UAV states using the Extended Kalman Filter are introduced. The second part describes how we designed a sliding mode controller considering the sensor measurement errors and discusses the sufficient conditions for the stability and formation system in the presence of state transfer time delays in the formation. The main motivation of this paper was to develop a hierarchical, globally stable sliding mode controller that could enable the considered vision-based multiple fixed-wing UAVs to achieve and maintain formation in the presence of measurement errors. To this end, the selected problem was first transformed into a state-tracking problem for UAVs in the neighborhood, and then the stability criterion was established using the Lyapunov stability theory. Finally, the effectiveness of the proposed control method was illustrated using three numerical arithmetic examples.