Finite-time stability and stabilization for highly nonlinear stochastic Markov jump systems

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Shiyu Zhong , Weihai Zhang
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引用次数: 0

Abstract

The research on finite-time stability (FTS) mainly focuses on linear and nonlinear systems, however, there are few studies on such problems for highly nonlinear systems. At present, most studies on FTS use the Lyapunov function method, and most of the results not only require the Lyapunov function in different modes to have the same feature, but also require the diffusion operators in different modes to be constrained by the same type of functions. This is somewhat restrictive to the selection of the Lyapunov function. Based on this, this paper concerns with FTS and asynchronous control of highly nonlinear stochastic Markov jump systems (HNSMJSs). Firstly, the criteria of mth moment finite-time stability (m-MFTS) for HNSMJSs in Lyapunov function form and parameter form are given and the asynchronous controller is provided to guarantee the mth moment finite-time stabilization (m-MFT stabilization). Moreover, HNSMJSs with deterministic time delay are extended to that with time-varying delay, and a more general result is given. Finally, three examples are provided to clarify the effectiveness of the proposed work.
高度非线性随机马尔可夫跳变系统的有限时间稳定性与镇定。
有限时间稳定性的研究主要集中在线性和非线性系统上,而对高度非线性系统的有限时间稳定性问题的研究很少。目前,关于FTS的研究大多采用Lyapunov函数方法,而且大多数结果不仅要求不同模态下的Lyapunov函数具有相同的特征,而且要求不同模态下的扩散算子受到相同类型函数的约束。这在一定程度上限制了李雅普诺夫函数的选择。在此基础上,研究了高度非线性随机马尔可夫跳变系统(HNSMJSs)的FTS和异步控制问题。首先,给出了HNSMJSs的第m矩有限时间稳定(m-MFTS)的Lyapunov函数形式和参数形式的判据,并给出了保证其第m矩有限时间稳定(m-MFT镇定)的异步控制器。并将具有确定性时滞的HNSMJSs推广到具有时变时滞的HNSMJSs,得到了更一般的结果。最后,提供了三个例子来说明所提出工作的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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