Sampled-Data Stabilization of Delayed Markov Jump Singular Systems and its Application

This article investigates the sampled-data stabilization problem of Markov jump singular systems (MJSSs) with time-varying delay. First, using state decomposition method, the MJSSs are transformed into the form of algebraic and differential equations. Next, an extended Lyapunov–Krasovskii functional (LKF) with looped function is constructed by considering the new state vectors. Meanwhile, a relaxed integral inequality is proposed to estimate the integral terms generated during derivation. Based on the extended LKF and the relaxed integral inequality, several improved stochastically admissible criteria are established with a few of decision variables. Then, the design method of desired controllers with sampled-data is proposed for the addressed MJSSs. Finally, several numerical examples are provided to confirm the superiority of the proposed results.