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We consider remote state estimation over a packet-dropping network. A new suboptimal filter is derived by minimizing the mean squared estimation error. The estimator is designed by solving one deterministic Riccati equation. Convergence of the estimation error covariance and mean square stability of the estimator are proved under standard assumptions. It is shown that the new estimator has smaller...
This paper is concerned with the linear estimation problems for discrete-time systems with random delayed observations. When the random delay is known online, i.e., time-stamped, the random delayed system is reconstructed as an equivalent delay-free one by using measurement reorganization technique, and then an optimal linear filter is presented based on Kalman filtering technique. However, the optimal...
This paper is concerned with estimation problem for discrete-time systems with packet dropping. A new optimal filter is derived by minimizing the mean squared estimation error. An optimal smoother is also derived in a similar way. Both estimators are designed by solving one deterministic Riccati equation. Both the convergence of the estimation error covariance and mean square stability of the estimator...
This paper presents a mean-square small gain theory for linear stochastic Ito systems with both state and control-dependent noise, what we have obtained improves and generalizes the previous results on the system with only state-dependent noise to more general models
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