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

Abstract

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 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$l_{2}-l_{\infty }$ </tex-math></inline-formula> 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.