IEEE Transactions on Automatic Control, Vol.61, No.1, 145-155, 2016
On Rates of Convergence for Markov Chains Under Random Time State Dependent Drift Criteria
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.
Keywords:Foster-Lyapunov criteria;Markov Chain Monte-Carlo (MCMC);Markov processes;networked control systems;stochastic stability