On the impact of model errors on input and state estimation in structural dynamic systems

Abstract

In applied structural dynamics, input and state estimation techniques are used to identify unmeasurable response quantities and unknown forces from limited sensor data. These estimators depend on mechanical state-space models, which can be inaccurate due to uncertainties in the systems' mass, damping, and stiffness (or equivalently, the modal parameters of a linear system). This work examines the impact of such model errors and their effects are characterized by a theoretical framework for error propagation to the estimated quantities. The results are exemplified in a numerical example of a mass-spring system. The characterization is a first step towards more focused attempts to develop algorithms in the realm of input and state estimation that are able to deal more robustly with numerical models subject to uncertainty.