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Nonlinear System Identification of Aeroelastic Systems: A Structure-detection Approach

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Identification and Control

Abstract

Identification methods for NARMAX models are applied to aeroelastic dynamics and its properties demonstrated via continuous-time simulations and experimental conditions. Identification of parametric nonlinear models involves estimating unknown parameters and detecting its underlying structure. Structure computation is concerned with selecting a subset of parameters to give a parsimonious description of the system that may afford greater insight into the functionality of the system or a simpler controller design. Structure-detection methods applicable to NARMAX modeling are applied to aeroelastic dynamics. Among other methods, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear systems. Simulation results from a nonlinear dynamic aircraft model demonstrate that methods developed for NARMAX structure computation provide good accuracy for selection of the exact model structure from an over-parameterized model description. Applicability of the method to more complex systems such as those encountered in aerospace applications is shown by identifying parsimonious system descriptions of the F/A-18 active aeroelastic wing (AAW) using flight-test data.

This work was prepared as part of the second author’s official duties as an employee of the U. S. Government and in accordance with 17 U.S.C. 105, is not available for copyright protection in the United States. NASA is the owner of any foreign copyright that can be asserted for the work. Copyright@2006 by NASA.

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Authors and Affiliations

  1. Aerostructures Branch, NASA Dryden Flight Research Center, Edwards, California, USA

    Sunil L. Kukreja & Martin J. Brenner

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  1. Sunil L. Kukreja
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  2. Martin J. Brenner
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Editors and Affiliations

  1. ICREA and Advanced Control Systems (SAC) ESAII, Universitat Politècnica de Catalunya, Terrassa, Barcelona, Spain

    Ricardo S. Sánchez Peña PhD

  2. Advanced Control Systems (SAC) ESAII, Universitat Politècnica de Catalunya, Terrassa, Barcelona, Spain

    Vicenç Puig Cayuela Dr Eng  & Joseba Quevedo Casín PhD  & 

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Kukreja, S.L., Brenner, M.J. (2007). Nonlinear System Identification of Aeroelastic Systems: A Structure-detection Approach. In: Sánchez Peña, R.S., Cayuela, V.P., Casín, J.Q. (eds) Identification and Control. Springer, London. https://doi.org/10.1007/978-1-84628-899-9_5

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  • DOI: https://doi.org/10.1007/978-1-84628-899-9_5

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