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System Identification of Smart Structures Using a Nonlinear WARMA Model

System identification (SI) for constructed structural systems has received a lot of attention with the continuous development of modern technologies. This thesis proposes a new nonlinear time series model for use in system identification (SI) of smart structures. The proposed model is implemented by the integration of a wavelet transform (WT) and nonlinear autoregressive moving average (NARMA) time series model. The approach demonstrates the efficient and accurate nonlinear SI of smart structures subjected to both ambient excitation and high impact load. To demonstrate the effectiveness of the wavelet-based NARMA modeling (WNARMA), smart structures equipped with magnetorheological (MR) dampers are investigated. The simulation results show that the computation of the WNARMA model is faster than that of the NARMA model without sacrificing the modeling accuracy. In addition, the WNARMA model is robust against noise in the data since it inherently has a denoising capacity.

Identiferoai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-theses-1006
Date04 January 2013
CreatorsKim, JungMi
ContributorsYeesock Kim, Advisor, Tahar El-Korchi, Committee Member,
PublisherDigital WPI
Source SetsWorcester Polytechnic Institute
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceMasters Theses (All Theses, All Years)

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