Event-Triggered Impulsive Control of Nonlinear Stochastic Systems With Exogenous Disturbances

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Robust and Nonlinear Control Pub Date : 2024-12-04 DOI:10.1002/rnc.7746
Linna Liu, Chenglong Pan, Jianyin Fang
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Abstract

In this work, the stability problem of nonlinear stochastic systems is investigated under exogenous disturbances through event-triggered impulsive control (ETIC). The ETIC strategy proposed in this paper incorporates three levels of events, taking into account four indicators: threshold, control-free index, inspection interval, and waiting time for stochastic systems, which is more practically significant and can effectively eliminate the Zeno behavior. By utilizing Lyapunov stability theory, stochastic analysis techniques, and some fundamental inequalities, sufficient conditions for the r th $$ r\mathrm{th} $$ moment input-to-state stability ( r $$ r $$ -ISS) and exponentially r $$ r $$ -ISS of the considered system can be achieved through the implementation of the designed ETIC. Then, the theoretical results are employed in actual nonlinear stochastic systems, leading to the establishment of LMI-based criteria for exponential r $$ r $$ -ISS. Ultimately, the feasibility of ETIC strategy is confirmed through two instances.

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具有外源扰动的非线性随机系统的事件触发脉冲控制
本文通过事件触发脉冲控制(ETIC)研究了外源扰动下非线性随机系统的稳定性问题。本文提出的ETIC策略将事件分为三个层次,同时考虑了随机系统的阈值、无控制指标、检查间隔和等待时间四个指标,更具有实际意义,可以有效地消除Zeno行为。通过运用李亚普诺夫稳定性理论、随机分析技术和一些基本不等式,的实现,可以得到所考虑系统的r - $$ r\mathrm{th} $$矩输入状态稳定性(r $$ r $$ -ISS)和指数r $$ r $$ -ISS的充分条件设计了ETIC。然后,将理论结果应用于实际的非线性随机系统,建立了基于lmi的指数r $$ r $$ -ISS准则。最后,通过两个实例验证了ETIC策略的可行性。
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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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