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Adaptive neuro-controller design based on MLP network

International Postgraduate Conference On Engineering (IPCE 2010), 16th - 17th October 2010 organized by Centre for Graduate Studies, Universiti Malaysia Perlis (UniMAP) at School of Mechatronic Engineering, Pauh Putra Campus, Perlis, Malaysia.

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Bibliographic Details
Main Authors: Norhayati, Mohd Noor, A. S., Hashim, Mohd Yusoff, Mashor, Prof. Dr., Siti Maryam, Sharun, Azian Azamimi, Abdullah
Other Authors: yati_yasin@yahoo.com
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2012
Subjects:
Back Propagation (BP) algorithm
Adaptive Neuro-Controller (ANC)
Recursive Least Square (RLS)
Adaptive system
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/21617
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spelling my.unimap-216172012-11-05T07:59:06Z Adaptive neuro-controller design based on MLP network Norhayati, Mohd Noor A. S., Hashim Mohd Yusoff, Mashor, Prof. Dr. Siti Maryam, Sharun Azian Azamimi, Abdullah yati_yasin@yahoo.com Back Propagation (BP) algorithm Adaptive Neuro-Controller (ANC) Recursive Least Square (RLS) Adaptive system International Postgraduate Conference On Engineering (IPCE 2010), 16th - 17th October 2010 organized by Centre for Graduate Studies, Universiti Malaysia Perlis (UniMAP) at School of Mechatronic Engineering, Pauh Putra Campus, Perlis, Malaysia. Back Propagation (BP) algorithm is the most commonly used algorithm for training artificial neural networks. But, it suffers from extensive computations, relatively slow convergence speed and possible divergence for certain conditions. The main objective of this paper was to compare the performance of BP algorithm and Recursive Least Square (RLS) algorithm for Adaptive Neuro-Controller (ANC). These algorithms are used to update the parameter of the ANC. A neural network model, called Multi Layered Perceptron (MLP) network is used for this ANC. The Model Reference Adaptive Control (MRAC) is used to generate the desired output path and to ensure the output of the controlled system follows the output of reference model. In this paper, the comparison between two algorithms is based on the convergence speed and robustness of the controller. These controllers have been tested using a linear and a nonlinear plant with several varying operating conditions. The simulation results show that RLS algorithm have better performance compared to BP algorithm. 2012-11-05T07:59:05Z 2012-11-05T07:59:05Z 2010-10-16 Working Paper 978-967-5760-03-7 http://hdl.handle.net/123456789/21617 en Proceedings of the International Postgraduate Conference on Engineering (IPCE 2010) Universiti Malaysia Perlis (UniMAP) Centre for Graduate Studies
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Back Propagation (BP) algorithm
Adaptive Neuro-Controller (ANC)
Recursive Least Square (RLS)
Adaptive system
spellingShingle Back Propagation (BP) algorithm
Adaptive Neuro-Controller (ANC)
Recursive Least Square (RLS)
Adaptive system
Norhayati, Mohd Noor
A. S., Hashim
Mohd Yusoff, Mashor, Prof. Dr.
Siti Maryam, Sharun
Azian Azamimi, Abdullah
Adaptive neuro-controller design based on MLP network
description International Postgraduate Conference On Engineering (IPCE 2010), 16th - 17th October 2010 organized by Centre for Graduate Studies, Universiti Malaysia Perlis (UniMAP) at School of Mechatronic Engineering, Pauh Putra Campus, Perlis, Malaysia.
author2 yati_yasin@yahoo.com
author_facet yati_yasin@yahoo.com
Norhayati, Mohd Noor
A. S., Hashim
Mohd Yusoff, Mashor, Prof. Dr.
Siti Maryam, Sharun
Azian Azamimi, Abdullah
format Working Paper
author Norhayati, Mohd Noor
A. S., Hashim
Mohd Yusoff, Mashor, Prof. Dr.
Siti Maryam, Sharun
Azian Azamimi, Abdullah
author_sort Norhayati, Mohd Noor
title Adaptive neuro-controller design based on MLP network
title_short Adaptive neuro-controller design based on MLP network
title_full Adaptive neuro-controller design based on MLP network
title_fullStr Adaptive neuro-controller design based on MLP network
title_full_unstemmed Adaptive neuro-controller design based on MLP network
title_sort adaptive neuro-controller design based on mlp network
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2012
url http://dspace.unimap.edu.my/xmlui/handle/123456789/21617
_version_ 1643793415329021952
score 13.222552

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