Decentralized Adaptive Control of Large-Scale Non-Affine Nonlinear Time-Delay Systems Using Wavelet Neural Networks

In this paper, a decentralized adaptive controller with using wavelet neural network is used for a class of large-scale nonlinear systems with time- delay unknown nonlinear non- affine subsystems. The entered interruptions in subsystems are considered nonlinear with time delay, this is closer the re...

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Main Authors: Elaheh Saeedi, Bahram Karimi, Mostafa Pourbehi
Format: Article
Language:English
Published: Najafabad Branch, Islamic Azad University 2014-07-01
Series:Journal of Intelligent Procedures in Electrical Technology
Subjects:
Online Access:http://jipet.iaun.ac.ir/pdf_7644_267c05798e67ba45248dcc6099451823.html
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spelling doaj-5d42e8e004cb420fb0ebf9290616dfc52020-11-25T01:56:36ZengNajafabad Branch, Islamic Azad UniversityJournal of Intelligent Procedures in Electrical Technology2322-38712345-55942014-07-015181524Decentralized Adaptive Control of Large-Scale Non-Affine Nonlinear Time-Delay Systems Using Wavelet Neural NetworksElaheh Saeedi0Bahram Karimi1Mostafa Pourbehi2Najafabad Branch, Islamic Azad UniversityMalek-Ashtar University of TechnologyIranKhodro TamIn this paper, a decentralized adaptive controller with using wavelet neural network is used for a class of large-scale nonlinear systems with time- delay unknown nonlinear non- affine subsystems. The entered interruptions in subsystems are considered nonlinear with time delay, this is closer the reality, compared with the case in which the delay is not considered for interruptions. In this paper, the output weights of wavelet neural network and the other parameters of wavelet are adjusted online. The stability of close loop system is guaranteed with using the Lyapanov- Krasovskii method. Moreover the stability of close loop systems, guaranteed tracking error is converging to neighborhood zero and also all of the signals in the close loop system are bounded. Finally, the proposed method, simulated and applied for the control of two inverted pendulums that connected by a spring and the computer results, show that the efficiency of suggested method in this paper.http://jipet.iaun.ac.ir/pdf_7644_267c05798e67ba45248dcc6099451823.htmlLarge- scale systemnon-affine nonlinear systemwavelet neural networkadaptive control
collection DOAJ
language English
format Article
sources DOAJ
author Elaheh Saeedi
Bahram Karimi
Mostafa Pourbehi
spellingShingle Elaheh Saeedi
Bahram Karimi
Mostafa Pourbehi
Decentralized Adaptive Control of Large-Scale Non-Affine Nonlinear Time-Delay Systems Using Wavelet Neural Networks
Journal of Intelligent Procedures in Electrical Technology
Large- scale system
non-affine nonlinear system
wavelet neural network
adaptive control
author_facet Elaheh Saeedi
Bahram Karimi
Mostafa Pourbehi
author_sort Elaheh Saeedi
title Decentralized Adaptive Control of Large-Scale Non-Affine Nonlinear Time-Delay Systems Using Wavelet Neural Networks
title_short Decentralized Adaptive Control of Large-Scale Non-Affine Nonlinear Time-Delay Systems Using Wavelet Neural Networks
title_full Decentralized Adaptive Control of Large-Scale Non-Affine Nonlinear Time-Delay Systems Using Wavelet Neural Networks
title_fullStr Decentralized Adaptive Control of Large-Scale Non-Affine Nonlinear Time-Delay Systems Using Wavelet Neural Networks
title_full_unstemmed Decentralized Adaptive Control of Large-Scale Non-Affine Nonlinear Time-Delay Systems Using Wavelet Neural Networks
title_sort decentralized adaptive control of large-scale non-affine nonlinear time-delay systems using wavelet neural networks
publisher Najafabad Branch, Islamic Azad University
series Journal of Intelligent Procedures in Electrical Technology
issn 2322-3871
2345-5594
publishDate 2014-07-01
description In this paper, a decentralized adaptive controller with using wavelet neural network is used for a class of large-scale nonlinear systems with time- delay unknown nonlinear non- affine subsystems. The entered interruptions in subsystems are considered nonlinear with time delay, this is closer the reality, compared with the case in which the delay is not considered for interruptions. In this paper, the output weights of wavelet neural network and the other parameters of wavelet are adjusted online. The stability of close loop system is guaranteed with using the Lyapanov- Krasovskii method. Moreover the stability of close loop systems, guaranteed tracking error is converging to neighborhood zero and also all of the signals in the close loop system are bounded. Finally, the proposed method, simulated and applied for the control of two inverted pendulums that connected by a spring and the computer results, show that the efficiency of suggested method in this paper.
topic Large- scale system
non-affine nonlinear system
wavelet neural network
adaptive control
url http://jipet.iaun.ac.ir/pdf_7644_267c05798e67ba45248dcc6099451823.html
work_keys_str_mv AT elahehsaeedi decentralizedadaptivecontroloflargescalenonaffinenonlineartimedelaysystemsusingwaveletneuralnetworks
AT bahramkarimi decentralizedadaptivecontroloflargescalenonaffinenonlineartimedelaysystemsusingwaveletneuralnetworks
AT mostafapourbehi decentralizedadaptivecontroloflargescalenonaffinenonlineartimedelaysystemsusingwaveletneuralnetworks
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