Maximizing Average Power Output of an Airborne Wind Energy Generator Under Parametric Uncertainties

This paper presents a controller for maximizing the time-averaged power output from an airborne wind energy generator in uncertain wind conditions. This system’s optimal energy output often involves flying in periodic figure-8 trajectories, but the precise optimal figure-8 shape is sensitive to environmental conditions, including wind speed. The literature presents controllers that are able to adapt to uncertainties, and this work expands on the current literature by using an extremum seeking based method. Extremum seeking is particularly well-suited for this application because of its well understood stability properties. In this work, extremum seeking is used to search through a family of optimal trajectories (computed offline) that correspond to discrete wind speeds. The controller is efficient in that it only searches for the optimum trajectory over the uncertain parameter (in this paper, wind speed). Results show that the controller converges to the optimal trajectory, provided it is initialized to a stable figure-8. The speed of convergence is dependent on the difference between the initial average power output and the optimal average power output.