Distributed Nonlinear Predictive Control for Unmanned Air-Ground Vehicles

This paper addresses the formation path tracking for a heterogeneous system made up of a steering car and a quadcopter. System modelling is based on Nonlinear Model Predictive Control (NMPC), which is a proper solution when considering a heterogeneous feet as not only it deals with non-linearities of the dynamic model but it is also a way to generate trajectories that can be communicated to other agents. Moreover, an Extended Kalman Filter (EKF) is employed to estimate the non-measurable ground robot state variables. Two separate simulations in Simulink for each agent have been carried out leading to promising results in terms of tracking errors. Indeed, tests show that the proposed solution allows the two vehicles to follow the reference aligned with a deviation of a few centimeters.