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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Najafabad Branch, Islamic Azad University
2014-07-01
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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 |
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1724979017288777728 |