Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/154490
Title: Event-triggered adaptive neural network controller for uncertain nonlinear system
Authors: Gao, Hui
Song, Yongduan
Wen, Changyun
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: 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
Journal: Information Sciences
Abstract: 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.
URI: https://hdl.handle.net/10356/154490
ISSN: 0020-0255
DOI: 10.1016/j.ins.2019.08.015
Rights: © 2019 Elsevier Inc. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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