CLC number: TP13
On-line Access: 2022-10-26
Received: 2021-11-29
Revision Accepted: 2022-10-26
Crosschecked: 2021-12-21
Cited: 0
Clicked: 2593
Citations: Bibtex RefMan EndNote GB/T7714
Zhiqian LIU, Xuyang LOU, Jiajia JIA. Event-triggered dynamic output-feedback control for a class of Lipschitz nonlinear systems[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(11): 1684-1699.
@article{title="Event-triggered dynamic output-feedback control for a class of Lipschitz nonlinear systems",
author="Zhiqian LIU, Xuyang LOU, Jiajia JIA",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="23",
number="11",
pages="1684-1699",
year="2022",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2100552"
}
%0 Journal Article
%T Event-triggered dynamic output-feedback control for a class of Lipschitz nonlinear systems
%A Zhiqian LIU
%A Xuyang LOU
%A Jiajia JIA
%J Frontiers of Information Technology & Electronic Engineering
%V 23
%N 11
%P 1684-1699
%@ 2095-9184
%D 2022
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2100552
TY - JOUR
T1 - Event-triggered dynamic output-feedback control for a class of Lipschitz nonlinear systems
A1 - Zhiqian LIU
A1 - Xuyang LOU
A1 - Jiajia JIA
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 23
IS - 11
SP - 1684
EP - 1699
%@ 2095-9184
Y1 - 2022
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2100552
Abstract: This paper investigates the problem of dynamic output-feedback control for a class of lipschitz nonlinear systems. First, a continuous-time controller is constructed and sufficient conditions for stability of the nonlinear systems are presented. Then, a novel event-triggered mechanism is proposed for the lipschitz nonlinear systems in which new event-triggered conditions are introduced. Consequently, a closed-loop hybrid system is obtained using the event-triggered control strategy. Sufficient conditions for stability of the closed-loop system are established in the framework of hybrid systems. In addition, an upper bound of a minimum inter-event interval is provided to avoid the Zeno phenomenon. Finally, numerical examples of a neural network system and a genetic regulatory network system are provided to verify the theoretical results and to show the superiority of the proposed method.
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