UAV energy extraction with incomplete atmospheric data using MPC

A nonlinear model predictive control strategy is presented for unmanned aerial vehicle (UAV) trajectory determination. The objective is to find optimal paths in the atmosphere by maximizing the UAV´s energy (kinetic and potential) over a finite but receding horizon. The main assumption is that the updraft distribution is unknown, creating a realistic situation. The updrafts are only estimated online using standard on-board inertial sensors. Real-time implementation of the algorithm is shown to be possible in principle.