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This paper is concerned with the

Analysis and synthesis of the networked systems has received much research attention in the last decade due to the wide applications of networked systems into the industrials, such as process control system, chemical systems, and remote surgery. Despite the advantages brought by the networked systems, various challenging problems occur, such as packet dropouts, communication delays, and medium access constraints. In the last few years, the state estimation for networks systems has become a hot research topic. Basically, there are state estimation algorithms: one is the Kalman filtering and the other one is the

On another research front line, Markovian jump systems have attracted significant attention from control society for many decades. This is due to the fact that such systems are shown to be appropriate and convenient to model a large number of practical systems that are subjected to abrupt variations in their structures, owing to sudden environmental disturbances, abrupt variations in the operating point of a nonlinear plant, and so on. Many works have been reported on the analysis and

In this paper, the

The notations used in this paper are standard. The

The structure of the considered filtering system is shown in Figure

The structure of networked systems.

Suppose there are

In the real networked systems, the delay may occur in a stochastic way; hence, a set of stochastic variables,

Let

Based on the above discussions, the filter input signal is

In order to derive the filtering error system, we rewrite state equation in (

Define

System (

System (

For a given scalar

A sufficient condition is firstly presented to guarantee the stability of the filtering error system.

For given scalars

We first consider the stability of the filtering error system (

It is seen that the right hand side of (

Now we consider the

It should be pointed out that Theorem

For given scalars

By pre- and postmultiplying (

In order to obtain the minimum

Consider a satellite yaw angles control system with noise perturbation, which is given by the following state-space representations [

Choosing

In real control systems, controller failure may occur. In this example, we only consider a partial failure case; that is, the real controller is taken as

Suppose the remote filter is designed to estimate the signal

In the simulation setup, we choose the zero initial conditions, and the noise signal is taken as

Trajectories of

Trajectory of

In this paper, the

The authors declare that there is no conflict of interests regarding the publication of this paper.

This work was supported by the open project of the State Key Laboratory of Industrial Control Technology under Grant no. ICT1409.

_{∞}estimation for uncertain systems with limited communication capacity

_{∞}filtering for semi-Markov jump systems with randomly occurring uncertainties and sensor failures