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...
Main Author: | Chua, Nigel Boon Hong. |
---|---|
Other Authors: | Sundararajan, Narasimhan |
Format: | Thesis |
Language: | English |
Published: |
2008
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/13113 |
Similar Items
-
Efficient sequential fuzzy-neural algorithms for aircraft fault-tolerant control
by: Rong, Haijun
Published: (2008) -
Reliable robust aircraft control against faults and saturations
by: Feng, Le
Published: (2008) -
Adaptive control of nonlinear dynamic system using fully tuned radial basis function neural networks : aircraft flight control applications
by: Li, Yan.
Published: (2008) -
Flight path optimization in free route airspace using A*Search
by: Goh, Leslie Peck Yong
Published: (2018) -
Optimisation of operation flight plan using genetic algorithm
by: Loh, Kai Leong.
Published: (2011)