Trajectory Tracking and Collision Avoidance Switching Control for Multi-UAV Based on DMPC

Multi-unmanned aerial vehicle (UAV) system often encounters sudden static or dynamic obstacle threats during flight. How to realize obstacle avoidance is one of the key problems that must be solved for multi-UAV system. Therefore, this paper proposes a distributed model prediction control algorithm with mode switching. Two control modes (the tracking mode and the collision avoidance mode) and their switching strategies are designed based on risk of collision. Among them, the tracking mode takes tracking trajectory as the goal, and the corresponding algorithm can ensure the asymptotic stability of the system, the collision avoidance mode takes collision avoidance as the primary goal, and collision avoidance constraints are introduced by triggering to achieve collision avoidance between the UAV and the obstacles. Compared with the traditional single-mode predictive control algorithm, the proposed method can make the UAVs avoid the pre-unknown large-scale obstacles more effectively, and has the advantages of low conservativeness and short computation time. Finally, the effectiveness of the method is verified using the simulation of six quadrotors.