控制理论(社会学)
李雅普诺夫函数
指数稳定性
事件(粒子物理)
计算机科学
控制器(灌溉)
理论(学习稳定性)
采样(信号处理)
随机过程
控制(管理)
非线性系统
数学
统计
人工智能
滤波器(信号处理)
生物
机器学习
物理
量子力学
计算机视觉
农学
作者
Fengzhong Li,Yungang Liu
出处
期刊:IEEE transactions on cybernetics
[Institute of Electrical and Electronics Engineers]
日期:2021-10-01
卷期号:51 (10): 5142-5155
被引量:9
标识
DOI:10.1109/tcyb.2019.2946169
摘要
This article is devoted to explore the periodic event-triggered stabilization for continuous-time stochastic systems, and to develop analysis tools/methods for stochastic periodic event-triggered control. Notably, without real-time monitoring of system behavior as in the scenario with continuous event evaluation, it is critical to delicately estimate and govern the execution/sampling error to achieve the desired system performance. This, under stochastic effects, would be substantially challenging, since the behavior of the stochastic system is hard to predict and is disparate between trials even with the same initial conditions. In this article, a framework of global stabilization via periodic event-triggered output-feedback is established: 1) a criterion condition based on the ISS-Lyapunov function is presented for the feasibility of the desired event-triggered stabilization; 2) both the asymptotic stabilization and exponential stabilization are achieved for the systems, with delicately specifying the periodic event-triggering mechanism; and 3) the involved analysis, without applying the well-known Lyapunov theorems, can serve as a pattern from estimating sampling and execution errors to assess the closed-loop stability for stochastic periodic event-triggered control. Moreover, based on the established framework, we contribute the stabilizing controller design via periodic event-triggered output-feedback for a class of stochastic nonlinear systems.
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