Event-triggered quantized-output state estimation for discrete singular Markovian jump systems

This article concentrates on the event-triggered (ET) quantized-output state estimation of discrete-time singular Markovian jump network systems (DSJNSs) with the disturbance input and interval time-varying delays. Initially, an augmented DSJNS model with network-induced delay is established by utilizing the quantized control and ET communication strategies. Then, based on the free-weighing matrix and stochastic analysis approaches, sufficient conditions are obtained such that a delayed DSJNS is stochastically H & INFIN;$$ {H}_{\infty } $$ admissible. Using separation matrix variables, ET quantized state estimators and ET gain matrix parameters are co-designed to ensure the stochastic H & INFIN;$$ {H}_{\infty } $$ admissibility of the DSJNS. Additionally, an electrical circuit example is given to verify the feasibility of the proposed technique.