Predictive control for soaring of unpowered autonomous UAVs

In this paper we propose an energy-harvesting controller design for a 3 degree-of-freedom glider in a nonlinear MPC framework. The glider is simulated within a generic atmospheric updraft environment with the aim of extracting the maximum amount of energy from the environment. We focus on conceptual feasibility at this stage and we take the realistic assumption that the glider is able to obtain updraft information only along the flight trajectory. The surrounding updraft distribution is then recursively estimated (online) by combining the measurements from the optimal trajectory with a heuristic search, if necessary. A variation of the standard grid search is used such that the grid spacing is altered depending on the updraft information along the glider’s flight path. Results from both standard and adaptive grid search approaches are presented. In abstract terms, this work can be viewed as finding optimal paths in uncertain vector fields.