数学
非线性系统
应用数学
理论(学习稳定性)
不稳定性
控制理论(社会学)
计算机科学
物理
控制(管理)
量子力学
机器学习
人工智能
机械
作者
Juliang Yin,Suiyang Khoo,Zhihong Man,Xinghuo Yu
出处
期刊:Automatica
[Elsevier BV]
日期:2011-10-07
卷期号:47 (12): 2671-2677
被引量:491
标识
DOI:10.1016/j.automatica.2011.08.050
摘要
This paper presents a new definition of finite-time stability for stochastic nonlinear systems. This definition involves stability in probability and finite-time attractiveness in probability. An important Lyapunov theorem on finite-time stability for stochastic nonlinear systems is established. A theorem extending the stochastic Lyapunov theorem is also proved. Moreover, an example and a lemma are presented to illustrate the scope of extension. A useful inequality, extended from Bihari’s inequality, is derived, which plays an important role in showing the Lyapunov theorem. Finally, a Lyapunov theorem on finite-time instability is proved, which states that almost surely globally asymptotical stability is not equivalent to finite-time stability for some stochastic systems. Two simulation examples are given to illustrate the theoretical analysis.
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