Model predictive control for a swarm of fixed wing UAVs

This paper describes an algorithm for the control of a swarm of UAVs based on decentralized MPC. For each UAV, our algorithm first determines the trajectory taking into account the obstacles and the constraints on the aircraft performance. Then basing on a robust MPC algorithm, optimal guidance laws are calculated and tracked by the UAVs by means of local PIDs controllers. Our approach also allows us to take into account moving obstacles and constraints on the minimum distance between the vehicles. Validation of the approach is obtained by means of simulations where for each UAV a 6-DOF model is used