Abstract
This paper is concerned with theH∞filtering for a class of networked Markovian jump systems with multiple communication delays. Due to the existence of communication constraints, the measurement signal cannot arrive at the filter completely on time, and the stochastic communication delays are considered in the filter design. Firstly, a set of stochastic variables is introduced to model the occurrence probabilities of the delays. Then based on the stochastic system approach, a sufficient condition is obtained such that the filtering error system is stable in the mean-square sense and with a prescribedH∞disturbance attenuation level. The optimal filter gain parameters can be determined by solving a convex optimization problem. Finally, a simulation example is given to show the effectiveness of the proposed filter design method.
Highlights
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
This paper is concerned with the H∞ filtering for a class of networked Markovian jump systems with multiple communication delays
Though the H∞ filtering for networked systems with stochastic delays was studied in [18], the authors assumed that the measurement signal is transmitted to the remote filter within a single packet
Summary
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. The authors in [1] studied the remote state estimation for the networked systems with missing observations They addressed this problem under the discrete Kalman filtering formulation and gave the statistical convergence properties of the estimation error covariance, showing the existence of a critical value for the arrival rate of the observations. It is well known that the Kalman filter is only applicable to the systems with a certain well-posed model, and the external noise is required to be a stochastic process with known statistical property. Though the H∞ filtering for networked systems with stochastic delays was studied in [18], the authors assumed that the measurement signal is transmitted to the remote filter within a single packet. The H∞ filtering problem is addressed for a class of networked Markovian jump systems with multiple communication delays.
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