@inproceedings{b9bb3d360625427bb2e745260ef02ebf,
title = "Output-only recursive identification of time-varying structures using a Gaussian process regression TARMA approach",
abstract = "This paper focuses on the problem of output-only recursive identification of time-varying structures. A kernelized time-dependent autoregressive moving average (TARMA) model is proposed by expanding the time-varying model parameters onto the basis set of kernel functions in a reproducing kernel Hilbert space. A Gaussian process regression TARMA identification scheme is subsequently proposed, allowing the Gaussian process regression to operate for vector TARMA models in a recursive manner. The proposed method is employed to identify a laboratory time-varying structure consisting of a simply supported beam and a sliding mass, and is assessed against an existing recursive pseudo-linear regression TARMA method via Monte Carlo experiments. The comparison demonstrates the superior achievable accuracy of the proposed Gaussian process regression TARMA approach.",
author = "Ma, {Z. S.} and L. Liu and Zhou, {S. D.} and F. Naets and W. Heylen and W. Desmet",
year = "2016",
language = "English",
series = "Proceedings of ISMA 2016 - International Conference on Noise and Vibration Engineering and USD2016 - International Conference on Uncertainty in Structural Dynamics",
publisher = "KU Leuven, Departement Werktuigkunde",
pages = "2859--2870",
editor = "Paul Sas and David Moens and {van de Walle}, Axel",
booktitle = "Proceedings of ISMA 2016 - International Conference on Noise and Vibration Engineering and USD2016 - International Conference on Uncertainty in Structural Dynamics",
note = "27th International Conference on Noise and Vibration Engineering, ISMA 2016 and International Conference on Uncertainty in Structural Dynamics, USD2016 ; Conference date: 19-09-2016 Through 21-09-2016",
}