H∞ fuzzy filtering of nonlinear systems with intermittent measurements

  • Authors:

  • Huijun Gao;Yan Zhao;James Lam;Ke Chen

  • Affiliations:

  • Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin, China;Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin, Heilongjiang, China;Department of Mechanical Engineering, University of Hong Kong, Hong Kong;Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

  • Venue:
  • IEEE Transactions on Fuzzy Systems
  • Year:
  • 2009

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Abstract

This paper is concerned with the problem of H∞ fuzzy filtering of nonlinear systems with intermittent measurements. The nonlinear plant is represented by a Takagi-Sugeno (T-S) fuzzy model. The measurements transmission from the plant to the filter is assumed to be imperfect, and a stochastic variable satisfying the Bernoulli random binary distribution is utilized to model the phenomenon of the missing measurements. Attention is focused on the design of an H∞ filter such that the filter er ror system is stochastically stable and preserves a guaranteed H∞ performance. A basis-dependent Lyapunov function approach is developed to design the H∞ filter. By introducing some slack matrix variables, the coupling between the Lyapunov matrix and the system matrices is eliminated, which greatly facilitates the filter-design procedure. The developed theoretical results are in the form of linear matrix inequalities (LMIs). Finally, an illustrative example is provided to show the effectiveness of the proposed approach.