Stabilization of discrete-time systems with stochastic sampling

This paper is concerned with the stabilization problem of discrete-time systems with stochastic sampling. It is assumed that there are a single-rate sampling in the plant input and two stochastic sampling rates in the controller input whose occurrence probabilities are given constants and satisfy a Bernoulli distribution. By Lyapunov function approach, a new sufficient condition is presented for the mean square asymptotic stability of the system. Based on this, the design procedure for stabilization controllers is proposed. Finally, an example is given to demonstrate the effectiveness of the proposed techniques.