Skip to Main content Skip to Navigation
Conference papers

A neural approach for fast simulation of flight mechanics

Abstract : Flight simulators have been part of aviation history since its beginning. With the development of modern aeronautics industry, flight simulators have gained an important place and the industry devoted to their manufacture has become significant. In the case of transportation aircraft, accurate mathematical models based on extensive experimental data have been developed by their manufacturers to optimize their aerodynamic and propulsive characteristics and to design efficient flight control systems. However, in the case of small general aviation aircraft this kind of knowledge is not commonly available and the design of accurate flight simulators can result in a tedious try and modify process until the simulator presents a qualitative behaviour close to the one of the real aircraft. This communication proposes through the use of neural networks a method to perform a direct estimation of the aerodynamic forces acting on aircraft. Artificial neural networks appear to be an appropriate numerical technique to achieve the mapping of these continuous relationships and detailed aerodynamics and thrust models should become no more mandatory to produce accurate flight simulation software.
Document type :
Conference papers
Complete list of metadatas

Cited literature [8 references]  Display  Hide  Download

https://hal-enac.archives-ouvertes.fr/hal-00938075
Contributor : Laurence Porte <>
Submitted on : Monday, June 23, 2014 - 4:29:37 PM
Last modification on : Tuesday, October 20, 2020 - 10:32:06 AM
Long-term archiving on: : Tuesday, September 23, 2014 - 10:40:10 AM

File

599.pdf
Publisher files allowed on an open archive

Identifiers

Citation

Giórgio Valmórbida, Wen Chi Lu, Felix Mora-Camino. A neural approach for fast simulation of flight mechanics. ANSS 2005, 38th Annual Simulation Symposium, Apr 2005, Sao Paulo, Brazil. pp 168 - 172, ⟨10.1109/ANSS.2005.8⟩. ⟨hal-00938075⟩

Share

Metrics

Record views

298

Files downloads

587