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Robust finite-horizon filtering of time-varying networked systems with error variance constraints

Hongli Dong, Zidong Wang*, Daniel W.C. Ho, Huijun Gao

*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

In this paper, the robust finite-horizon filtering problem is investigated for a class of uncertain nonlinear discrete time-varying stochastic systems with multiple missing measurements and error variance constraints. The stochastic nonlinearities are described by statistical means which can cover several classes of well-studied nonlinearities. The measurement missing phenomenon is also considered. Sufficient conditions are derived for a finite-horizon filter to satisfy the estimation error variance constraints. These conditions are expressed in terms of the feasibility of a series of recursive linear matrix inequalities (RLMIs). An illustrative simulation example is given to show the the effectiveness of the proposed algorithm. © 2010 IEEE.
Original languageEnglish
Title of host publication2010 8th IEEE International Conference on Control and Automation, ICCA 2010
Pages590-595
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event8th IEEE International Conference on Control and Automation (IEEE ICCA 2010) - Xiamen, China
Duration: 9 Jun 201011 Jun 2010

Conference

Conference8th IEEE International Conference on Control and Automation (IEEE ICCA 2010)
PlaceChina
CityXiamen
Period9/06/1011/06/10

Research Keywords

  • Discrete time-varying systems
  • Error variance constraint.
  • Recursive matrix inequalities
  • Stochastic nonlinearities

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