Adaptive Distributed Fuzzy Control for Prescribed-Time Formation of Multiple Unmanned Aerial Vehicles

This study investigated an adaptive distributed prescribed-time fuzzy formation control for quadrotor multi-unmanned aerial vehicles (UAVs). The trajectories of two attitude subsystems were represented through intermediate control variables by considering the underactuated characteristics of UAVs. Furthermore, by utilizing fuzzy logic systems (FLSs) to approximate nonlinear functions and employing the auxiliary function method, this study proposes a distributed adaptive prescribed-time fuzzy formation control scheme. This approach enables real-time updates of the position and speed information for both the leader and follower UAVs. The proposed adaptive prescribed-time fuzzy controller ensures that multi-UAVs reach their formation positions within a prescribed time and that attitude angles can track the reference signals. Finally, the effectiveness of the proposed scheme was verified through a simulation example.