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An eigensystem realization algorithm for modal parameter identification and model reduction

Juang, Jer-Nan, Pappa, Richard S.·1985·Journal of Guidance, Control, and Dynamics

Abstract

A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system modes and noise modes. For illustration of the algorithm, examples are shown using simulation data and experimental data for a rectangular grid structure.

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Metadata

Authors
Juang, J.-N., & Pappa, R. S.
Venue
Journal of Guidance, Control, and Dynamics
Published
1985-09
Volume
8
Issue
5
Pages
620-627
ISSN
  • 0731-5090 (ISSN-L)
  • 1533-3884
OpenAlex
W2168090960
Cited by
2,762
References
1
FWCI
99.81
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: An eigensystem realization algorithm for modal parameter identification and model reduction. https://app.cochat.ai/papers/10.2514/3.20031
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Juang, J.-N., & Pappa, R. S. (1985). An eigensystem realization algorithm for modal parameter identification and model reduction. Journal of Guidance, Control, and Dynamics. https://doi.org/10.2514/3.20031

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.