Robust H-Infinity Filtering for Networked Control Systems with Markovian Jumps and Packet Dropouts

Abstract

This paper deals with the H ∞ filtering problem for uncertain networked control systems. In the study, network-induced delays, limited communication capacity due to signal quantization and packet dropout are all taken into consideration. The finite distributed delays with probability of occurrence in a random way is introduced in the network.The packet dropout is described by a Bernoulli process. The system is modeled as Markovian jumps system with partially known transition probabilities. A full-order filter is designed to estimate the system state. By linear inequality approach, a sufficient condition is derived for the resulting filtering error system to be mean square stable with a prescribed H ∞ performance level. Finally, a numerical example is given to illustrate the effectiveness and efficiency of the proposed design method.

H∞ Filter Design for Networked Control Systems: A Markovian Jump System Approach

“…Two models in the simulation are set as those data in (29). In the model, the transition probabilities are π ij � 0.3 0.7 0.4 0.6 , the initial value of β is 0.5, and the initial condition is set to zero.…”

“…Definition 1 (see [29]). A filter error system (5) is stochastically stable when ω(k) � 0. ere x 0 ∈ R and r 0 ∈ l, and the following inequality exists:…”

“…Definition 2 (see [29]). Give a scalar c > 0, assume that system (5) is stochastically stable, and (5) also can meet an…”

Output‐based event‐triggered control of networked systems subject to bilateral packet dropouts

“…The first one is to model a system with data packet losses by using the Markovian jump system. 11 In the second method, the packet loss behaviors are described by the independent Bernoulli's distribution random variables. 12 Furthermore, the dropouts are considered as a special case of time-delay.…”

“…The methods of handling stochastic data losses are generally classified into four categories. The first one is to model a system with data packet losses by using the Markovian jump system 11 . In the second method, the packet loss behaviors are described by the independent Bernoulli's distribution random variables 12 .…”