Aeroservoelastic Model Validation and Test Data Analysis of the F/a-18 Active Aeroelastic Wing
Author | : National Aeronautics and Space Administration (NASA) |
Publisher | : Createspace Independent Publishing Platform |
Total Pages | : 36 |
Release | : 2018-06-20 |
ISBN-10 | : 1721585214 |
ISBN-13 | : 9781721585212 |
Rating | : 4/5 (14 Downloads) |
Download or read book Aeroservoelastic Model Validation and Test Data Analysis of the F/a-18 Active Aeroelastic Wing written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-06-20 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model validation and flight test data analysis require careful consideration of the effects of uncertainty, noise, and nonlinearity. Uncertainty prevails in the data analysis techniques and results in a composite model uncertainty from unmodeled dynamics, assumptions and mechanics of the estimation procedures, noise, and nonlinearity. A fundamental requirement for reliable and robust model development is an attempt to account for each of these sources of error, in particular, for model validation, robust stability prediction, and flight control system development. This paper is concerned with data processing procedures for uncertainty reduction in model validation for stability estimation and nonlinear identification. F/A-18 Active Aeroelastic Wing (AAW) aircraft data is used to demonstrate signal representation effects on uncertain model development, stability estimation, and nonlinear identification. Data is decomposed using adaptive orthonormal best-basis and wavelet-basis signal decompositions for signal denoising into linear and nonlinear identification algorithms. Nonlinear identification from a wavelet-based Volterra kernel procedure is used to extract nonlinear dynamics from aeroelastic responses, and to assist model development and uncertainty reduction for model validation and stability prediction by removing a class of nonlinearity from the uncertainty. Brenner, Martin J. and Prazenica, Richard J. Armstrong Flight Research Center NASA/TM-2003-212021, H-2526, NAS 1.15:212021