Nonlinear Black-Box Modeling of Aeroelastic Systems Using Structure Detection Approach: Application to F/A-18 Aircraft Data
| Autor: | Sunil L. Kukreja, Martin J. Brenner |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Engineering
business.industry Applied Mathematics Computation System identification Aerospace Engineering Model description Nonlinear system Autoregressive model Space and Planetary Science Control and Systems Engineering Control theory Moving average Black box Autoregressive–moving-average model Electrical and Electronic Engineering business |
| Zdroj: | Journal of Guidance, Control, and Dynamics. 30:557-564 |
| ISSN: | 1533-3884 0731-5090 |
| DOI: | 10.2514/1.20835 |
| Popis: | Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for "black-box" modeling is not well known to the flight-test community but may be of critical importance in the development of robust, parsimonious models. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. Structure detection methods applicable to nonlinear autoregressive, moving average exogenous modeling are applied to aeroelastic dynamics and their properties demonstrated via continuous-time simulations of experimental conditions. Simulation results from a nonlinear dynamic model of aircraft structural free-play demonstrate that methods developed for nonlinear autoregressive, moving average exogenous structure computation provide a high degree of accuracy for selection of the exact model structure from an overparameterized model description. Applicability of these methods to the F/A-18 active aeroelastic wing using flight-test data is shown by identifying a parsimonious system description with a high percent fit for cross-validated data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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