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

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: Theses and Dissertations
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
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Institution: Nanyang Technological University
Language: English
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.

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