  Airborne wind energy (AWE) systems are tethered flying devices that harvest
wind resources at higher altitudes which are not accessible to conventional
wind turbines. In order to become a viable alternative to other renewable
energy technologies, AWE systems are required to fly reliably for long periods
of time without manual intervention while being exposed to varying wind
conditions. In the present work a methodology is presented, which augments an
existing baseline controller with a prediction and prevention methodology to
improve the resilience of the controller against these external disturbances.
In the first part of the framework, upset conditions are systematically
generated in which the given controller is no longer able to achieve its
objectives. In the second part, the generated knowledge is used to synthesize a
model that predicts upsets beforehand. Eventually, this allows to trigger an
avoidance maneuver which keeps the AWE system operational, however, leads to a
lower power production. The methodology is applied to the specific case of
tether rupture prediction and prevention. Simulation results are used to
demonstrate that the presented methodology leads indeed to a predictable
economic benefit over systems without the proposed baseline controller
augmentation.
