On Rates of Convergence for Markov Chains Under Random Time State Dependent Drift Criteria

被引:4
|
作者
Zurkowski, Ramiro [1 ]
Yueksel, Serdar [1 ]
Linder, Tamas [1 ]
机构
[1] Queens Univ, Dept Math & Stat, Kingston, ON K7L 3N6, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Foster-Lyapunov criteria; Markov Chain Monte-Carlo (MCMC); Markov processes; networked control systems; stochastic stability; MULTICLASS QUEUING-NETWORKS; STOCHASTIC STABILITY; SUBGEOMETRIC RATES; LINEAR-SYSTEMS; STABILIZATION;
D O I
10.1109/TAC.2015.2447251
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Many applications in networked control require intermittent access of a controller to a system, as in event-triggered systems or information constrained control applications. Motivated by such applications and extending previous work on Lyapunov-theoretic drift criteria, we establish both subgeometric and geometric rates of convergence for Markov chains under state dependent random time drift criteria. We quantify how the rate of ergodicity, nature of Lyapunov functions, their drift properties, and the distributions of stopping times are related. We finally study an application in networked control.
引用
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页码:145 / 155
页数:11
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