HH∞ filtering for sampled-data stochastic systems with limited capacity channel

This paper investigates the H∞H∞ filtering problem for sampled-data stochastic systems with limited capacity channel. The considered plant is described by a class of Itô stochastic systems subject to external disturbance. The output measurements are sampled and quantized, and then transmitted through a network medium. The aim of this paper is focused on the design of full order filters by using the quantized sampled outputs. In sampled-data systems, the value of the sampled signal increases abruptly at sampling times, and traditional filter design results based on time-independent Lyapunov–Krasovskii functionals (or Lyapunov–Razumikhin functions) may be conservative. The main contribution of this paper is to propose a new type of time-dependent   Lyapunov function for Itô stochastic systems which does not increase in sampling times due to its special mathematical structure. Based on this approach, sufficient conditions for the existence of the proposed filter are established such that the filtering error system is stochastically stable and preserves a guaranteed H∞H∞ performance. A numerical example is provided to illustrate the effectiveness of the proposed filtering technique in this paper.