This paper deals with the development of a robust optimal control framework for a
previously developed multi-body ski jumper simulation model by the authors. This framework is
used to model uncertainties acting on the jumper during his jump, e.g., wind or mass, to enhance
the performance, but also to increase the fairness and safety of the competition. For the uncertainty
modeling the method of generalized polynomial chaos together with the discrete expansion by
stochastic collocation is applied: This methodology offers a very flexible framework to model
multiple uncertainties using a small number of required optimizations to calculate an uncertain
trajectory. The results are then compared to the results of the Latin-Hypercube sampling method to
show the correctness of the applied methods. Finally, the results are examined with respect to two
major metrics: First, the influence of the uncertainties on the jumper, his positioning with respect to
the air, and his maximal achievable flight distance are examined. Then, the results are used in a
further step to quantify the safety of the jumper.
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This paper deals with the development of a robust optimal control framework for a
previously developed multi-body ski jumper simulation model by the authors. This framework is
used to model uncertainties acting on the jumper during his jump, e.g., wind or mass, to enhance
the performance, but also to increase the fairness and safety of the competition. For the uncertainty
modeling the method of generalized polynomial chaos together with the discrete expansion by
stochastic colloca...
»