NDLI: The application of separable least square algorithms based on global nonlinear for the parametric identifications of airplane flutter model

Content Provider	IEEE Xplore Digital Library
Author	Yao Jie Zhu Yong-hong Wang Jang-hong
Copyright Year	2012
Description	Author affiliation: School of the mechanical and electronic, Jingdezhen Ceramic Institute, Jiangxi, China, 333403 (Yao Jie; Zhu Yong-hong; Wang Jang-hong)
Abstract	In this paper, we extend the biased compensated least-squares method (CLS) to get the nonlinear separable least squares (NSLS) when the observed input-output data are corrupted with noise. The nonlinear separable least square algorithm is adopted for aircraft flutter modal parameter identification under noisy environment. Combing with a rational transfer function model, the identification of system with noisy data is transformed into a nonlinear separable least square problem. Using this algorithm, the noise variance parameters and the model parameters can be obtained separately. The simulation with real flight test data shows the efficiency of the algorithm.
Starting Page	2539
Ending Page	2543
File Size	440081
Page Count	5
File Format	PDF
ISBN	9781457720734
e-ISBN	9781457720741
DOI	10.1109/CCDC.2012.6243051
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Airplanes Least-squares method Nonlinear separate least-squares Atmospheric modeling Noise Transfer functions Flutter Mathematical model Noise measurement Parameter identification Equations
Content Type	Text
Resource Type	Article

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