Non-Statistical Based Robust Identification of a Lightly Damped Flexible Using Kautz Orthonormal Basis Functions

Use of time domain input-output data and the deterministic specification of system uncertainties for the robust identification of lightly damped flexible beams was investigated. Stochastic embedding (SE), model error modeling (MEM) and set membership (SM) are applied for robust identification. The i...

Full description

Saved in:
Bibliographic Details
Published in:Journal of low frequency noise, vibration, and active control vibration, and active control, 2008-01, Vol.27 (3), p.203-203
Main Authors: Esmaeilsabzali, Hadi, Montazeri, Allahyar, Poshtan, Javad, Jahedmotlagh, Mohammadreza
Format: Article
Language:English
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Use of time domain input-output data and the deterministic specification of system uncertainties for the robust identification of lightly damped flexible beams was investigated. Stochastic embedding (SE), model error modeling (MEM) and set membership (SM) are applied for robust identification. The input-output data are processed and amplified using 3560c pulse system and 2706 amplifier. In order to simulate measurement noise, the output signal has been corrupted by a normally distributed Gaussian random signal with the variance of 1 percent. For the parallelotopic algorithm, the identification results are better, and the tightness of the uncertainty bound is adequate, but the real model is not covered by the uncertainty bound at some frequencies.
ISSN:1461-3484