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Chinese Journal of Mechanical Engineering
Erschienen in: Chinese Journal of Mechanical Engineering 2/2017

17.03.2017 | Original Article

Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

verfasst von: Zhisai MA, Li LIU, Sida ZHOU, Frank NAETS, Ward HEYLEN, Wim DESMET

Erschienen in: Chinese Journal of Mechanical Engineering | Ausgabe 2/2017

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Abstract

The problem of linear time-varying(LTV) system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the “frozen-time” assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stability-preserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system’s stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam experimental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides a new way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.
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Metadaten
Titel
Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach
verfasst von
Zhisai MA
Li LIU
Sida ZHOU
Frank NAETS
Ward HEYLEN
Wim DESMET
Publikationsdatum
17.03.2017
Verlag
Chinese Mechanical Engineering Society
Erschienen in
Chinese Journal of Mechanical Engineering / Ausgabe 2/2017
Print ISSN: 1000-9345
Elektronische ISSN: 2192-8258
DOI
https://doi.org/10.1007/s10033-017-0075-7

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