A time-domain nonlinear system identification method based on multiscale dynamic partitions

Lee, YS; Tsakirtzis, S; Vakakis, AF; Bergman, LA; McFarland, DM

dc.contributor.author	Lee, YS	en
dc.contributor.author	Tsakirtzis, S	en
dc.contributor.author	Vakakis, AF	en
dc.contributor.author	Bergman, LA	en
dc.contributor.author	McFarland, DM	en
dc.date.accessioned	2014-03-01T01:35:03Z
dc.date.available	2014-03-01T01:35:03Z
dc.date.issued	2011	en
dc.identifier.issn	0025-6455	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20953
dc.subject	Complexification-averaging technique	en
dc.subject	Empirical mode decomposition	en
dc.subject	Intrinsic modal Oscillator	en
dc.subject	Intrinsic mode function	en
dc.subject	Nonlinear system identification	en
dc.subject	Slow flow model	en
dc.subject.classification	Mechanics	en
dc.subject.other	Complexification-averaging technique	en
dc.subject.other	Empirical mode decomposition	en
dc.subject.other	Intrinsic modal Oscillator	en
dc.subject.other	Intrinsic Mode functions	en
dc.subject.other	Non-linear system identification	en
dc.subject.other	Slow flow	en
dc.subject.other	Dynamical systems	en
dc.subject.other	Nonlinear systems	en
dc.subject.other	Signal processing	en
dc.subject.other	Time series	en
dc.subject.other	Time series analysis	en
dc.subject.other	Time domain analysis	en
dc.title	A time-domain nonlinear system identification method based on multiscale dynamic partitions	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/s11012-010-9327-7	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s11012-010-9327-7	en
heal.language	English	en
heal.publicationDate	2011	en
heal.abstract	Based on a theoretical foundation for empirical mode decomposition, which dictates the correspondence between the analytical and empirical slow-flow analyses, we develop a time-domain nonlinear system identification (NSI) technique. This NSI method is based on multiscale dynamic partitions and direct analysis of measured time series, and makes no presumptions regarding the type and strength of the system nonlinearity. Hence, the method is expected to be applicable to broad classes of applications involving time-variant/time- invariant, linear/nonlinear, and smooth/non-smooth dynamical systems. The method leads to nonparametric reduced order models of simple form; i.e., in the form of coupled or uncoupled oscillators with time-varying or time-invariant coefficients forced by nonhomogeneous terms representing nonlinear modal interactions. Key to our method is a slow/fast partition of transient dynamics which leads to the identification of the basic fast frequencies of the dynamics, and the subsequent development of slow-flow models governing the essential dynamics of the system.We provide examples of application of the NSI method by analyzing strongly nonlinear modal interactions in two dynamical systems with essentially nonlinear attachments. © 2010 Springer Science+Business Media B.V.	en
heal.publisher	SPRINGER	en
heal.journalName	Meccanica	en
dc.identifier.doi	10.1007/s11012-010-9327-7	en
dc.identifier.isi	ISI:000292567500001	en
dc.identifier.volume	46	en
dc.identifier.issue	4	en
dc.identifier.spage	625	en
dc.identifier.epage	649	en