Sampled-data stabilization for a class of stochastic nonlinear systems with Markovian switching based on the approximate discrete-time models

The mean-square exponential stability of a class of stochastic differential equations with Markovian switching(SDEwMS) by sampled-data control is investigated. We introduce a new controller design idea for such kind of systems based on its approximate discrete-time model(ADTM). Comparing with the existing results, this controller design method(CDM) is simpler and easier to calculate. Meanwhile, We study the multi-step model error between the SDEwMS and its Euler-Maruyama(EM) model. The effectiveness of our results is demonstrated by a numerical simulation.