Corridor Tracking Using Model Predictive Control for Urban Air Mobility

This study proposes a linear model predictive control algorithm for tracking an air corridor while avoiding fixed obstacles such as areas restricted from weather or terrain features. Urban air mobility operating in complex urban environments must ensure high safety. It is not easy to anticipate every potential scenario beforehand and pre-generate trajectories accordingly. Hence, the proposed algorithm assumes continuous flight at a constant velocity and incorporates a real-time perception of unexpected fixed obstacles, dynamically adjusting constraints to track the desired trajectory. Urban air mobility operating on predefined corridors must maneuver without deviating from its original route. To ensure that the urban air mobility&quots maneuvering is not hindered by the constraints on the corridor, a flexible corridor strategy is applied. This study uses a point-mass model to perform a parametric study on the size of the prediction horizon through multiple simulations. The proposed algorithm confirms the ability to avoid obstacles keeping the existing corridor as much as possible using a flexible corridor and an appropriate prediction horizon.