This study is concerned with the development of a robust open-loop optimal control (ROC) framework that distributes different generalized polynomial chaos (gPC) sub-problems from the non-intrusive stochastic collocation (SC) method. This distributed open-loop optimal control (DOC) approach yields a number of smaller open-loop optimal control problems (OCPs) that can be solved independently of each other and are only connected by a small number of connection variables. These connection variables are introduced based on the specifics of the used cost and constraint functions and describe the coupling in the gPC expansion when e.g., calculating the variance. Overall, the definition as a DOC problem yields a faster and more reliable way to solve the ROC problem than by a full, connected problem. Here, the study shows the applicability of the proposed method in an air race example with the optimization of mean values and variances.     «

This study is concerned with the development of a robust open-loop optimal control (ROC) framework that distributes different generalized polynomial chaos (gPC) sub-problems from the non-intrusive stochastic collocation (SC) method. This distributed open-loop optimal control (DOC) approach yields a number of smaller open-loop optimal control problems (OCPs) that can be solved independently of each other and are only connected by a small number of connection variables. These connection variables...     »