Experimental validation of repetitive disturbance estimation and model predictive control for multi UAVs

In this paper, we propose a method to estimate the disturbance information using repetitive technique based on a disturbance map. The disturbance map is shared among unmanned aerial vehicles (UAVs) during platoon flight. Shared map improves the estimated accuracy of disturbance observer via repetitive technique, referred as repetitive estimation. Using the estimated disturbance information, the disturbance map is updated on real-time. The disturbance information can be referred in model predictive control (MPC) as prior information. As the result, the disturbance influence will be suppressed effectively. The validity of the proposed method is verified via experiments using two UAVs.