Over the past decade, a large number of academics and start-ups have devoted them- selves to developing kites, or airplanes on tethers, as a renewable energy source. Determining the trajectories the kite should follow is a modeling and optimization challenge. We present a dynamic model and analyse how uncertainty affects the resulting optimization problem. We show how measurements can be used to rapidly correct the model-based optimal trajectories in real time. This novel real-time optimization approach does not rely on intensive online computation. Rather, it uses knowledge of the structure of the optimal solution, which can be studied offline.
Dominique Bonvin, Alejandro Gabriel Marchetti