Event-triggered finite-time state estimation for discrete singular Markovian systems with quantization

Abstract

The problem of finite-time state estimation is discussed for discrete singular Markov jump network systems (DSMNSs) based on event-triggered (ET) quantization control strategy. According to the ET network communication and quantization control schemes, an augmented DSMNS model with time-delays is first constructed. Employing stochastic Lyapunov functional and introducing relaxation matrix variables, sufficient conditions are established for the DSMNS to be singularly stochastic finite-time bounded. Besides, the ET gain matrices and ET quantized feedback controllers are co-designed by decoupling matrix variable parameters so that the augmented DSMNS is singularly stochastic finite-time bounded with a specified performance index. Eventually, the effectiveness of the proposed scheme is verified and evaluated by a numerical simulation.