Wavelet Neural Network with PLS Feature Extraction and its Application in Aerodynamic Modeling for Aircraft Stall

Xu Sheng Gan; Xue Qin Tang; Hai Long Gao

doi:10.4028/www.scientific.net/AMM.602-605.3131

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605Wavelet Neural Network with PLS Feature Extraction...

Wavelet Neural Network with PLS Feature Extraction and its Application in Aerodynamic Modeling for Aircraft Stall

Abstract:

An aerodynamic modeling method based on WNN with Partial Least Squares (PLS) is proposed. In the method, PLS first is applied to extract the feature of original aerodynamic data samples, and then the obtained feature is used to establish the WNN aerodynamic model for aircraft stall from flight test data. Simulation results are given to illustrate that the proposed method is effective and feasible.

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Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

3131-3134

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.3131

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Online since:

August 2014

Authors:

Xu Sheng Gan*, Xue Qin Tang, Hai Long Gao

Keywords:

Aerodynamics Model, Aircraft Stall, Feature Extraction, Partial Least Squares, Wavelet Neural Network

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* - Corresponding Author

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