Linear estimation of physical parameters with subsampled and delayed data

Abstract

An improved algorithm for the estimation of physical parameters with sub-sampled and delayed data is here presented. It shows a much better accuracy than the state-of-the-art when the sampling time of data acquisition T s is much higher than the discretization step T s c that should be used to get a highly accurate discrete model, i.e. T s ≫ T s c , which is a common situation in multi-body and finite-element modelling applications. Moreover, the method proposed is capable of compensating delays between different acquisition channels. For the numerical experiments we focus on a mainstream class of models in applied mechanics, i.e. linear elasto-dynamics.