Cart (Loading....) | Create Account
Close category search window
 

Real-time identification of missile aerodynamics using a linearised Kalman filter aided by an artificial neural network

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
$31 $31
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

1 Author(s)
Horton, M.P. ; Flight Dynamics Dept., British Aerosp. Defence Ltd., Bristol, UK

The paper investigates the problem of real-time identification of aerodynamic derivatives in a guided missile application. This application provides a severe test for any parameter estimator, since it has to identify the linearised parameters of a multivariable, nonlinear, time variant, noisy plant, which is initially unstable and then becomes lightly damped. Initially, two radically different approaches are taken by designing both a linearised Kalman filter (LKF) estimator and an artificial neural network (ANN) based estimator. A hybrid estimator is then formed by an LKF, which is aided by the ANN. This produces a new estimator which has superior performance to those from which it is derived. The performance of these estimators is assessed with a nonlinear single plane model against eight types of engagements

Published in:

Control Theory and Applications, IEE Proceedings -  (Volume:144 ,  Issue: 4 )

Date of Publication:

Jul 1997

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.