Higher dimensional uncertainty modeling with polyhedral clouds

By Dr. Martin Fuchs

Uncertainty modeling in real-life applications faces some major difficulties: how to deal with a lack of information, how to cope with high dimensional problems and how to use valuable information provided in the form of unformalized expert knowledge.

We introduce the clouds formalism as means to process available uncertainty information reliably, even if limited in amount and possibly lacking a formal description. We provide a worst-case
analysis with confidence regions of relevant scenarios which can be embedded in robust spacecraft design optimization problem formulations.