Covariance-Based Realization Algorithm for the Identification of Aeroelastic Dynamics
| Autor: | Daniel N. Miller, Martin J. Brenner, Raymond A. de Callafon |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Computer science
Applied Mathematics Aerospace Engineering White noise Covariance Space and Planetary Science Control and Systems Engineering Colors of noise Control theory Singular value decomposition Electrical and Electronic Engineering Eigensystem realization algorithm Algorithm Realization (systems) Subspace topology Parametric statistics |
| Zdroj: | Journal of Guidance, Control, and Dynamics. 35:1169-1177 |
| ISSN: | 1533-3884 0731-5090 |
| DOI: | 10.2514/1.55770 |
| Popis: | Anovel subspace system identificationmethod based on covariance estimates and inspired by classical realization techniques is presented that constructs system estimates frommeasured input–output data. The resulting algorithm allows for the identification of parametric systemmodels from data sets of large signal dimension and is applicable to data perturbed by colored noise and acquired in closed-loop operation due to the unbiased estimation of crosscovariance functions, even in low signal-to-noise conditions. The algorithm is applied to data measured onboard an F/A-18. The results demonstrate the effectiveness of the algorithm in efficiently computing accurate, unbiased linear dynamic models from large data sets of high-dimensional signal sets obtained from aircraft in flight. |
| Databáze: | OpenAIRE |
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