Linear estimation of physical parameters with subsampled and delayed data

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摘要

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 Ts is much higher than the discretization step Tsc that should be used to get a highly accurate discrete model, i.e. Ts≫Tsc, 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.

论文关键词:00-01,99-00,System identification,Parameter estimation,State-space models,Continuous-time models,Elasto-dynamics

论文评审过程:Received 16 October 2016, Revised 18 September 2017, Accepted 19 September 2017, Available online 2 October 2017, Version of Record 13 October 2017.

论文官网地址:https://doi.org/10.1016/j.cam.2017.09.036