Neuro-flight controllers for aircraft using minimal, radial basis function (RBF) neural networks

This thesis presents the implementation of a newly developed minimal Radial Basis Function ( RBF ) neural network using the Minimal Resource Allocation Network ( M-RAN ) sequential learning algorithm for flight control system ap-plications. F-8 and F-16 fighter aircraft models are used in this thesi...

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Bibliographic Details
Main Author:	Chua, Nigel Boon Hong.
Other Authors:	Sundararajan, Narasimhan
Format:	Thesis
Language:	English
Published:	2008
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Aeronautical engineering::Air navigation
Online Access:	http://hdl.handle.net/10356/13113

Description
Summary:	This thesis presents the implementation of a newly developed minimal Radial Basis Function ( RBF ) neural network using the Minimal Resource Allocation Network ( M-RAN ) sequential learning algorithm for flight control system ap-plications. F-8 and F-16 fighter aircraft models are used in this thesis for the neuro-flight control system application studies. Three flight control architectures using M-RAN have been developed in this study.

Neuro-flight controllers for aircraft using minimal, radial basis function (RBF) neural networks

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