FALCON.M

Robustness against stochastic uncertainties is highly important for aerospace applications. By means of generalized Polynomial Chaos and Stochastic Collocation (gPC-SC), FALCON.m is capable of accounting for uncertain parameters, both in post-optimal analyses and in inherently robust chance-constrained optimization. Furthermore, sensitivity-based approaches to robustness are under investigation... In real-world applications the effects of parameter variations are highly relevant. FALCON.m supports such analyses by efficiently calculating post-optimal sensitivities with respect to problem parameters and control histories. This includes first-order sensitivities of the states, outputs and constraints, as well as second-order sensitivities of the objective... Since its initial release in 2014, FALCON.m has proven its viability in academic research and real-world industry applications. We continue to improve and extend the framework as part of our ongoing research projects.

Primary location: Garching Germany