By Topic

Notice of Retraction
Global nonlinear aerodynamic model identification based on NARMAX model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Hui Xia ; Department of Automation, Nanjing University of Science and Technology, China ; Xianyu Meng ; Qingwei Chen

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

A new method for global nonlinear aerodynamic model identification is presented. Aerodynamic model of aircraft is analyzed, and a simple and effective aerodynamic model is presented. The aerodynamic model of aircraft is then depicted in NARMAX (Nonlinear Auto Regressive Moving Average model with eXogenous inputs) form inside a Linear Regression framework. The items and coefficients of the aerodynamic model are identified in a sort of recursive algorithm simultaneously. The new identification method is used to identify a global nonlinear aerodynamic model of the F-16 fighter aircraft which uses the wind-tunnel data from NASA-Langley wind-tunnel tests on a scale model of an F-16 airplane. The identified aerodynamic model is compared directly with NASA wind tunnel model which uses polynomial model, showing that the identification method in this paper can identify the nonlinear aerodynamic coefficients and predict the aerodynamic parameters in higher precision.

Published in:

2010 International Conference on Computer Application and System Modeling (ICCASM 2010)  (Volume:9 )

Date of Conference:

22-24 Oct. 2010