State Estimation for Networked Systems With Markov Driven Transmission and Buffer Constraint

This article investigates the problem of state estimation for discrete-time systems with a Markov driven transmission strategy. A buffer with limited capacity is used to store the latest measurements, and they are transmitted simultaneously once the system accesses to the shared channel. A buffer-dependent smart estimator is then proposed to process the received measurements. A convex sufficient condition concerning the exponential mean-square stability and the $l_{2}-l_{\infty }$ performance is established for the estimation error system to design the estimator gains. Finally, two examples are presented to illustrate the effectiveness of the derived result under different conditions.