Robust H∞ filtering for a class of nonlinear networked systems with multiple stochastic communication delays and packet dropouts

  • Authors:

  • Hongli Dong;Zidong Wang;Huijun Gao

  • Affiliations:

  • Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin, China, and College of Electrical and Information Engineering, Daqing Petroleum Institute, Daqing, Chi ...;Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, U.K.;Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin, China

  • Venue:
  • IEEE Transactions on Signal Processing
  • Year:
  • 2010

Quantified Score

Hi-index 35.69

Visualization

Abstract

In this paper, the robust H∞ filtering problem is studied for a class of uncertain nonlinear networked systems with both multiple stochastic time-varying communication delays and multiple packet dropouts. A sequence of random variables, all of which are mutually independent but obey Bernoulli distribution, are introduced to account for the randomly occurred communication delays. The packet dropout phenomenon occurs in a random way and the occurrence probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution in the interval [0 1]. The discrete-time system under consideration is also subject to parameter uncertainties, state-dependent stochastic disturbances and sector-bounded nonlinearities. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square while the disturbance rejection attenuation is constrained to a give level by means of the H∞ performance index. Intensive stochastic analysis is carried out to obtain sufficient conditions for ensuring the exponential stability as well as prescribed H∞ performance for the overall filtering error dynamics, in the presence of random delays, random dropouts, nonlinearities, and the parameter uncertainties. These conditions are characterized in terms of the feasibility of a set of linear matrix inequalities (LMIs), and then the explicit expression is given for the desired filter parameters. Simulation results are employed to demonstrate the effectiveness of the proposed filter design technique in this paper.