Intermittent Sampled-Data Stabilization of Highly Nonlinear Delayed Stochastic Networks via Periodic Self-Triggered Strategy

被引：12

作者：

Zhou, Hui ^{[1
]}

Li, Shufan ^{[2
]}

Park, Ju H. ^{[2
]}

Li, Wenxue ^{[2
]}

机构：

[1] Harbin Inst Technol, Dept Math, Weihai 264209, Peoples R China

[2] Yeungnam Univ, Dept Elect Engn, Gyongsan 38541, South Korea

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2024年 / 69卷 / 10期

基金：

新加坡国家研究基金会;

关键词：

Robots; Stochastic systems; Delays; Generators; Delay effects; Vectors; Nonlinear systems; Highly nonlinear systems; intermittent control; sampled-data control; stabilization; time delay;

D O I：

10.1109/TAC.2024.3393839

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This article considers the stabilization issue of highly nonlinear delayed stochastic networks (HNDSNs) based on periodic self-triggered intermittent control under sampled-data (PICS) for the first time. Therein, the linear growth condition is taken off, and some PICS-based stabilization conditions in previous works are weakened. It is worth pointing out that the existing results are suitable for highly nonlinear networks neither based on PICS nor considering the time-varying delay. Given this, the existence of the unique global solution of HNDSNs under PICS is discussed, and then a stabilization criterion is derived by utilizing a modified Lyapunov function. After that, a numerical example of central pattern generator networks for a hexapod robot is given for demonstration.

引用

页码：7223 / 7230

页数：8

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