Stochastic stabilization of switching diffusion systems via an intermittent control strategy with delayed and sampled-data observations

This paper investigates the intermittent stochastic stabilization of switching diffusion systems (SDSs) via sampled data with time delays of state and mode. First, by virtue of analysis techniques for Markov chains, some estimates of the solutions for SDSs are derived. Second, with the aid of iteration by steps, a sufficient criterion is proposed for intermittent stochastic stabilization via sampled data with time delays of state and mode. Finally, a simulation example verifies the effectiveness of the theoretical results. (c) 2022 Elsevier B.V. All rights reserved.

Automated summary

This paper investigates the intermittent stochastic stabilization of switching diffusion systems (SDSs) via sampled data with time delays of state and mode. The solutions for SDSs are derived by using analysis techniques for Markov chains. A sufficient criterion for intermittent stochastic stabilization via sampled data with time delays of state and mode is proposed with the aid of iteration by steps. The theoretical results are verified by a simulation example.