The most common control algorithm used in commercial Unmanned Aerial Vehicles’ (UAVs) autopilots is the Proportional Integrative Derivative controller. The PID-based controller cannot handle changes in UAV dynamics and the presence of wind disturbances; in this latter case a PID parameters re-tuning is necessary. UAVs’ flight performance is affected by exogenous disturbances and additive noise, existing in a real operative environment. Dealing with always more demanding requirements of flight maneuvers, a robust Model Predictive Control (MPC) approach is proposed, which is able to handle external disturbances (as gusts or wind distubances) and parametric uncertainties (as variations in mass, flight conditions or payload).