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A new approach to nonlinear modeling of highly maneuverable aircraft using neural networks
Saghafi, F ; Sharif University of Technology | 2006
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- Type of Document: Article
- Publisher: Curran Associates Inc , 2006
- Abstract:
- Artificial Neural networks offer viable solution to identification and modeling of aerospace dynamic systems. This paper proposes a new approach to the nonlinear modeling of agile aircraft which is applicable to develop flight simulators. In contrary to classical methods, neural-network-based modeling of aircraft dynamics does not require any aerodynamic or propulsion model and a few flight test measured data suffice. The obtained model is shown valid for arbitrary pilot inputs within a region of mach-altitude around the pre-specified flight condition
- Keywords:
- Aerodynamics ; Flight simulators ; Identification (control systems) ; Models ; Neural networks ; Nonlinear systems ; Aircraft dynamics ; Classical methods ; Flight conditions ; Non-linear model ; Propulsion models ; RNN ; Simulation ; Viable solutions ; Aircraft
- Source: 25th Congress of the International Council of the Aeronautical Sciences 2006, Hamburg, 3 September 2006 through 8 September 2006 ; Volume 5 , 2006 , Pages 3134-3140
- URL: http://icas.org/ICAS_ARCHIVE/ICAS2006/PAPERS/443.PDF