Event-Triggered Sampling Problem for Exponential Stability of Stochastic Nonlinear Delay Systems Driven by Levy Processes

• 成果类型: Article
• 署名作者: Zhu, Quanxin
• 署名单位: Hunan Normal University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3448128
• 发表日期: 2025
• 页码: 1176-1183
• 关键词: STOCHASTIC PROCESSES; Stochastic systems; STABILITY; PROCESS CONTROL; control theory; DELAYS; Neural Networks; Event-triggered feedback control; event-triggered sampling; practically pth moment exponential stability; stochastic neural network; stochastic nonlinear delay systems (SNDSs) driven by Levy processes

摘要

This article mainly discusses the stabilization issue for a class of stochastic nonlinear delay systems driven by Levy processes. Based on a novel event-triggered strategy and stochastic analysis techniques, we solve the practically pth moment exponential stability problem of the considered system. Comparing with those previous results, we do not require the global Lipschitz condition and do not use the linear matrix inequality method. Also, different from many results for stochastic systems in discrete-time or stochastic systems in continuous-time driven by the usual Brownian motion, our results are mainly concentrated on the event-triggered sampling problem of stochastic systems in continuous-time driven by Levy processes, and delays are also involved. Moreover, we establish the pth moment exponential stabilization criterion for any p>0, which is more general and meaningful for practical application than those results only considering the case of p=2. Finally, our results are applied to stochastic neural networks driven by Levy processes and are checked with two examples.