Event-triggered adaptive neural network controller for uncertain nonlinear system
In this paper, an event-triggered adaptive controller, consisting of a basic adaptive neural network controller and an event-triggered mechanism, is developed for a class of single-input and single-output high-order nonlinear systems with neural network approximation. Both the static and the dynamic...
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sg-ntu-dr.10356-1544902021-12-23T07:17:53Z Event-triggered adaptive neural network controller for uncertain nonlinear system Gao, Hui Song, Yongduan Wen, Changyun School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Event-Triggered Adaptive Neural Networks In this paper, an event-triggered adaptive controller, consisting of a basic adaptive neural network controller and an event-triggered mechanism, is developed for a class of single-input and single-output high-order nonlinear systems with neural network approximation. Both the static and the dynamic event-triggered mechanisms are proposed in our design, without the input-state stability (ISS) assumption which is needed in most existing results. It is shown that the proposed methods can ensure that the closed loop system is globally stable. The minimal inter-event time internal is lower bounded by a positive number so that no Zeno behavior occurs. Finally, the numerical simulations are presented to illustrate our theory. 2021-12-23T07:17:53Z 2021-12-23T07:17:53Z 2020 Journal Article Gao, H., Song, Y. & Wen, C. (2020). Event-triggered adaptive neural network controller for uncertain nonlinear system. Information Sciences, 506, 148-160. https://dx.doi.org/10.1016/j.ins.2019.08.015 0020-0255 https://hdl.handle.net/10356/154490 10.1016/j.ins.2019.08.015 2-s2.0-85070241637 506 148 160 en Information Sciences © 2019 Elsevier Inc. All rights reserved. |
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Engineering::Electrical and electronic engineering Event-Triggered Adaptive Neural Networks Gao, Hui Song, Yongduan Wen, Changyun Event-triggered adaptive neural network controller for uncertain nonlinear system |
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In this paper, an event-triggered adaptive controller, consisting of a basic adaptive neural network controller and an event-triggered mechanism, is developed for a class of single-input and single-output high-order nonlinear systems with neural network approximation. Both the static and the dynamic event-triggered mechanisms are proposed in our design, without the input-state stability (ISS) assumption which is needed in most existing results. It is shown that the proposed methods can ensure that the closed loop system is globally stable. The minimal inter-event time internal is lower bounded by a positive number so that no Zeno behavior occurs. Finally, the numerical simulations are presented to illustrate our theory. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Gao, Hui Song, Yongduan Wen, Changyun |
format |
Article |
author |
Gao, Hui Song, Yongduan Wen, Changyun |
author_sort |
Gao, Hui |
title |
Event-triggered adaptive neural network controller for uncertain nonlinear system |
title_short |
Event-triggered adaptive neural network controller for uncertain nonlinear system |
title_full |
Event-triggered adaptive neural network controller for uncertain nonlinear system |
title_fullStr |
Event-triggered adaptive neural network controller for uncertain nonlinear system |
title_full_unstemmed |
Event-triggered adaptive neural network controller for uncertain nonlinear system |
title_sort |
event-triggered adaptive neural network controller for uncertain nonlinear system |
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2021 |
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https://hdl.handle.net/10356/154490 |
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1720447205161041920 |