Model Predictive Formation Tracking-Containment Control for Multi-UAVs With Obstacle Avoidance

This article investigates the formation tracking-containment control problem for multiple unmanned aerial vehicles (UAVs), while considering collision avoidance in the three-dimensional (3-D) environment. A distributed model predictive formation control method is developed for UAVs with obstacle avoidance. Unlike most existing trajectory tracking control schemes, the proposed method is derived from a smooth shifting function and a distributed Lyapunov-based model predictive controller, together with two collision-free functions, to obtain an improved control algorithm with the following characteristics: 1) the swarm system of UAVs realizes the cooperative hunting process from tracking formation to containing formation, fencing a target to their convex hull; 2) the Lyapunov-based model predictive formation control method inherits the stability properties of backstepping technique and adopts the receding horizon optimization of model predictive control (MPC) technique; and 3) by exploiting the Lyapunov-based MPC algorithm and collision-free functions, the swarm system of UAVs can avoid collision with obstacles or collision with each other in 3-D scenarios with multiple obstacles. Finally, the simulation and comparison results confirm that the proposed controller outperforms the traditional backstepping controller in terms of safety and tracking performance.