Updating nonlinear dynamical models using response measurements only

Status	已發表Published
	Updating nonlinear dynamical models using response measurements only
	Yuen K.-V.1; Beck J.L.2
	2003-12-01
Source Publication	Proceedings of the ASME Design Engineering Technical Conference
Volume	5 B
Pages	1593-1600
Abstract	A spectral density approach for the identification of linear systems is extended to nonlinear dynamical systems using only incomplete noisy response measurements. A stochastic model is used for the uncertain input and a Bayesian probabilistic approach is used to update the uncertainties in the model parameters. The proposed spectral-based approach utilizes important statistical properties of the Fast Fourier Transform and their robustness with respect to the probability distribution of the response signal in order to calculate the updated probability density function for the parameters of a nonlinear model conditional on the measured response. This probabilistic approach is well suited for the identification of nonlinear systems and does not require huge amounts of dynamic data. The formulation is presented directly for multiple-degree-of freedom systems. Examples using simulated data for a Duffing oscillator and a four-DOF inelastic structure are presented to illustrate the proposed approach.
URL	View the original
Language	英語English
Fulltext Access	View Full-Text via Scopus
Document Type	Conference paper
Collection	University of Macau
Affiliation	1.Universidade de Macau 2.California Institute of Technology
First Author Affilication	University of Macau
Recommended Citation GB/T 7714	Yuen K.-V.,Beck J.L.. Updating nonlinear dynamical models using response measurements only[C], 2003, 1593-1600.
APA	Yuen K.-V.., & Beck J.L. (2003). Updating nonlinear dynamical models using response measurements only. Proceedings of the ASME Design Engineering Technical Conference, 5 B, 1593-1600.

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