Hybrid representations for complex dynamical stochastic systems: Coupled non-parametric and parametric models

摘要

Parametric modeling of stochastic systems has proven useful for systems with well-defined and well structured sources of uncertainty. The suitability of such models is usually indicated by small levels of uncertainty associated with their parameters. The class of so-called non-parametric stochastic models was recently introduced in mechanics to address this specific issue, and has proven useful in treating problems whose level of uncertainty is high, involving spatially distributed sources of uncertainty. This paper presents a coupling technique, adapted to the receptance Frequency Response Function (FRF) matrix, for combining these two approaches. This will be useful for the analysis of complex dynamical systems having spatially non-homogeneous uncertainty that is otherwise difficult to analyze.