  Models of complex systems often consist of multiple interconnected
subsystem/component models that are developed by multi-disciplinary teams of
engineers or scientists. To ensure that such interconnected models can be
applied for the purpose of simulation and/or control, a reduced-order model for
the interconnected dynamics is needed. In the scope of this paper, we pursue
this goal by subsystem reduction to warrant modularity of the reduction
approach. Clearly, by reducing the complexity of the subsystem models, not only
the accuracy of the subsystem models is affected, but, consequently, also the
accuracy of the interconnected model. It is typically difficult to predict a
priori how the interconnected model accuracy is affected precisely by the
subsystem reduction. In this work, we address this challenge by introducing a
top-down approach which enables the translation of given accuracy requirements
of the interconnected system model to accuracy requirements at subsystem model
level, by using mathematical tools from robust performance analysis. This
allows for the independent reduction of subsystem models while guaranteeing the
desired accuracy of the interconnected model. In addition, we show how this
top-down approach can be used to significantly reduce the interconnected model
in an illustrative structural dynamics case study.
