We consider the problem of remote estimation with time delay and multiplicative noise for multichannel systems. First, we apply the reorganized innovation analysis approach to construct the original delay system into a new delay-free system. Secondly, the delay-free system will be reconstructed by the quadratic filtering method to obtain an augmented system. Then, Kalman filtering theory and projection formula are used to solve two Riccati equations and one Lyapunov equation for the augmented system, and the quadratic filter for the measurement delay system on the packet loss network can be obtained. Finally, we use a numerical example to illustrate the effectiveness of the method
In this note, we study optimal estimation design for sampled linear systems where the sensors measur...
Published version of an article in the journal: Mathematical Problems in Engineering. Also available...
In this paper, we consider Kalman filtering over a packet-delaying network. Given the probability di...
International audienceIn this paper, with regards to discrete-time networked control systems with in...
This paper studies an optimal state estimation (Kalman filtering) problem under the assumption that ...
We consider remote state estimation over a packet-dropping network. A new suboptimal filter is deriv...
Abstract This paper investigates the problem of real-time estimation for one kind of linear time inv...
This paper investigates the linear minimum mean square error estimation for discrete-time Markovian ...
Abstract—This paper investigates the problem of robust estimation for uncertain systems subject to l...
This paper studies the remote filtering problem over a packet-dropping network. A general multiple-i...
This paper is concerned with estimation problem for discrete-time systems with packet dropping. A ne...
The discrete-time state estimation problem is studied for networked control systems subject to rando...
The least-squares linear estimation problem using covariance information is addressed in discrete-ti...
This paper studies the steady-state Kalman filtering over the random delay and packet drop channel, ...
International audienceNetwork Controlled Systems are becoming very popular today. However, the use o...
In this note, we study optimal estimation design for sampled linear systems where the sensors measur...
Published version of an article in the journal: Mathematical Problems in Engineering. Also available...
In this paper, we consider Kalman filtering over a packet-delaying network. Given the probability di...
International audienceIn this paper, with regards to discrete-time networked control systems with in...
This paper studies an optimal state estimation (Kalman filtering) problem under the assumption that ...
We consider remote state estimation over a packet-dropping network. A new suboptimal filter is deriv...
Abstract This paper investigates the problem of real-time estimation for one kind of linear time inv...
This paper investigates the linear minimum mean square error estimation for discrete-time Markovian ...
Abstract—This paper investigates the problem of robust estimation for uncertain systems subject to l...
This paper studies the remote filtering problem over a packet-dropping network. A general multiple-i...
This paper is concerned with estimation problem for discrete-time systems with packet dropping. A ne...
The discrete-time state estimation problem is studied for networked control systems subject to rando...
The least-squares linear estimation problem using covariance information is addressed in discrete-ti...
This paper studies the steady-state Kalman filtering over the random delay and packet drop channel, ...
International audienceNetwork Controlled Systems are becoming very popular today. However, the use o...
In this note, we study optimal estimation design for sampled linear systems where the sensors measur...
Published version of an article in the journal: Mathematical Problems in Engineering. Also available...
In this paper, we consider Kalman filtering over a packet-delaying network. Given the probability di...