Stabilization for networked control systems with random sampling periods and random delays by Markov chains

This paper investigates the stabilization of networked control systems(NCSs). The controller-to-actuator (C-A) random delays and random sampling periods are modeled as Markov chains. The focus is to design a two-mode-dependent controller that depends on not only the current sampling period but also the last C-A delay at the controller node. The resulting closed-loop systems are special discrete-time jump linear systems with two modes. Then, the transition probabilities are assumed partially accessible, the stochastic stability is established. Further, the state feedback controller is designed via the iterative linear matrix inequality (LMI) approach.