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

成果类型:
Article
署名作者:
Zhou, Hui; Li, Shufan; Park, Ju H.; Li, Wenxue
署名单位:
Harbin Institute of Technology; Yeungnam University
刊物名称:
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
ISSN/ISSBN:
0018-9286
DOI:
10.1109/TAC.2024.3393839
发表日期:
2024
页码:
7223-7230
关键词:
robots Stochastic systems DELAYS Generators Delay effects vectors Nonlinear systems Highly nonlinear systems intermittent control sampled-data control stabilization time delay
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.
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