Details
| Original language | English |
|---|---|
| Pages (from-to) | 1326-1338 |
| Number of pages | 13 |
| Journal | Journal of Engineering Mechanics - ASCE |
| Volume | 138 |
| Issue number | 11 |
| Early online date | 15 Oct 2012 |
| Publication status | Published - 1 Nov 2012 |
| Externally published | Yes |
Abstract
Modeling errors, represented as uncertainty associated with the parameters of a mathematical model, inevitably exist in the process of constructing a theoretical model of real structures and limit the practical application of system identification. They are usually represented either in a deterministic manner or in a probabilistic way. However, if the available information is uncertain but of a nonprobabilistic nature, as it may emerge from a lack of knowledge about the sources and characteristics of model uncertainties, a third type of approach may be useful. Presented in this paperis an approach to treat modeling errors with the aid of intervals, resulting in bounded values for the identified parameters. Compared with the traditional identification procedures where model-based forward dynamic analysis is often involved, computing bounded time history responses from a computational model with interval parameters is avoided. Two required submatrices are firstly extracted from identified state-space models by applying a subspace identification method to the measurements, and then interval analysis is performed upon these two matrices to estimate the bounded uncertainty in the identified parameters. The effectiveness of the proposed methodology is evaluated through numerical simulationof a linear multipleedegree-of-freedom (MDOF) system when modeling errors in the mass and damping parameters are taken into account. The results show the ability of the proposed method to maintain sharp enclosures of the identified stiffness parameters.
Keywords
- Interval analysis, Modeling errors, State space, Structural dynamics, Subspace identification method, System identification, Uncertainty estimation
ASJC Scopus subject areas
- Engineering(all)
- Mechanics of Materials
- Engineering(all)
- Mechanical Engineering
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In: Journal of Engineering Mechanics - ASCE, Vol. 138, No. 11, 01.11.2012, p. 1326-1338.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Interval analysis for system identification of linear mdof structures in the presence of modeling errors
AU - Zhang, M. Q.
AU - Beer, M.
AU - Koh, C. G.
PY - 2012/11/1
Y1 - 2012/11/1
N2 - Modeling errors, represented as uncertainty associated with the parameters of a mathematical model, inevitably exist in the process of constructing a theoretical model of real structures and limit the practical application of system identification. They are usually represented either in a deterministic manner or in a probabilistic way. However, if the available information is uncertain but of a nonprobabilistic nature, as it may emerge from a lack of knowledge about the sources and characteristics of model uncertainties, a third type of approach may be useful. Presented in this paperis an approach to treat modeling errors with the aid of intervals, resulting in bounded values for the identified parameters. Compared with the traditional identification procedures where model-based forward dynamic analysis is often involved, computing bounded time history responses from a computational model with interval parameters is avoided. Two required submatrices are firstly extracted from identified state-space models by applying a subspace identification method to the measurements, and then interval analysis is performed upon these two matrices to estimate the bounded uncertainty in the identified parameters. The effectiveness of the proposed methodology is evaluated through numerical simulationof a linear multipleedegree-of-freedom (MDOF) system when modeling errors in the mass and damping parameters are taken into account. The results show the ability of the proposed method to maintain sharp enclosures of the identified stiffness parameters.
AB - Modeling errors, represented as uncertainty associated with the parameters of a mathematical model, inevitably exist in the process of constructing a theoretical model of real structures and limit the practical application of system identification. They are usually represented either in a deterministic manner or in a probabilistic way. However, if the available information is uncertain but of a nonprobabilistic nature, as it may emerge from a lack of knowledge about the sources and characteristics of model uncertainties, a third type of approach may be useful. Presented in this paperis an approach to treat modeling errors with the aid of intervals, resulting in bounded values for the identified parameters. Compared with the traditional identification procedures where model-based forward dynamic analysis is often involved, computing bounded time history responses from a computational model with interval parameters is avoided. Two required submatrices are firstly extracted from identified state-space models by applying a subspace identification method to the measurements, and then interval analysis is performed upon these two matrices to estimate the bounded uncertainty in the identified parameters. The effectiveness of the proposed methodology is evaluated through numerical simulationof a linear multipleedegree-of-freedom (MDOF) system when modeling errors in the mass and damping parameters are taken into account. The results show the ability of the proposed method to maintain sharp enclosures of the identified stiffness parameters.
KW - Interval analysis
KW - Modeling errors
KW - State space
KW - Structural dynamics
KW - Subspace identification method
KW - System identification
KW - Uncertainty estimation
UR - http://www.scopus.com/inward/record.url?scp=84876896176&partnerID=8YFLogxK
U2 - 10.1061/(ASCE)EM.1943-7889.0000433
DO - 10.1061/(ASCE)EM.1943-7889.0000433
M3 - Article
AN - SCOPUS:84876896176
VL - 138
SP - 1326
EP - 1338
JO - Journal of Engineering Mechanics - ASCE
JF - Journal of Engineering Mechanics - ASCE
SN - 0733-9399
IS - 11
ER -