数学
控制理论(社会学)
马尔可夫链
非线性系统
随机微分方程
控制(管理)
国家(计算机科学)
功能(生物学)
期限(时间)
离散时间和连续时间
应用数学
计算机科学
马尔可夫过程
李雅普诺夫函数
算法
物理
量子力学
进化生物学
生物
统计
机器学习
人工智能
作者
Chunhui Mei,Chen Fei,Mingxuan Shen,Weiyin Fei,Xuerong Mao
标识
DOI:10.1016/j.ins.2022.01.027
摘要
In this article, it is proved that feedback controllers can be designed to stabilize nonlinear neutral stochastic systems with Markovian switching (NSDDEwMS in short) only by using discrete observed state sequences. Due to the superlinear coefficients, the neutral term and the discrete observation data, many routine methods and techniques for the study of stochastic systems are not applicable. A new Lyapunov functional is constructed by using multiple M-matrices to prove that a given unstable NSDDEwMS can be stabilized if the control function can be designed to meet a couple of easy-to-be-verified rules. Finally, an example is given to illustrate the feasibility of the theoretical results.
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