实现随机严格反馈半马尔可夫跃迁系统几乎确定稳定性的周期性间歇控制

IF 3.7 2区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Chang Gao , Yu Xiao , Hao Dong , Beibei Guo
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引用次数: 0

摘要

本文研究了周期性间歇控制(PIC)下一类随机严格反馈半马尔可夫跃迁系统(SSSJS)的几乎确定稳定性(ASS)问题。这是首次在严格反馈系统中研究这种控制方法和动态特性。首先,根据 SSSJS 的结构特性,逐步设计出虚拟控制器,并最终推导出实际控制器。此外,利用随机分析理论和多重 Lyapunov 函数方法,我们得到了通过 PIC 实现 ASS 的充分条件,这些条件与控制宽度和控制周期有着密切的关系。凭借依赖于系统状态的多重 Lyapunov 函数,可以有效降低模式无关情况下的保守性。最后,通过仿真实例说明了上述结果的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Periodic intermittent control for almost sure stability of stochastic strict-feedback semi-Markov jump systems

In this paper, we investigate the issue of almost sure stability (ASS) for a class of stochastic strict-feedback semi-Markov jump systems (SSSJSs) under periodic intermittent control (PIC). This control method and dynamic properties are studied for the first time in strict-feedback systems. First of all, based on the structural properties of the SSSJSs, virtual controllers are designed step by step and eventually deduced into the actual controller. Furthermore, by using stochastic analysis theory and multiple Lyapunov function method, we obtain sufficient conditions for ASS via PIC, which have a close relationship with control width and control period. By virtue of multiple Lyapunov functions that depend on the system states, the conservatism caused by mode-independent cases can be reduced effectively. Finally, the effectiveness of the presented results is illustrated by simulation examples.

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来源期刊
Nonlinear Analysis-Hybrid Systems
Nonlinear Analysis-Hybrid Systems AUTOMATION & CONTROL SYSTEMS-MATHEMATICS, APPLIED
CiteScore
8.30
自引率
9.50%
发文量
65
审稿时长
>12 weeks
期刊介绍: Nonlinear Analysis: Hybrid Systems welcomes all important research and expository papers in any discipline. Papers that are principally concerned with the theory of hybrid systems should contain significant results indicating relevant applications. Papers that emphasize applications should consist of important real world models and illuminating techniques. Papers that interrelate various aspects of hybrid systems will be most welcome.
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