Robust filtering with randomly varying sensor delay: the finite-horizon case

Authors:
Fuwen Yang;Zidong Wang;Gang Feng;Xiaohui Liu
Affiliations:
School of Inf. Science and Eng., East China Univ. of Science and Technology, Shanghai, China and Dept. of Inf. Systems and Computing, Brunel Univ., Uxbridge, Middlesex, UK;Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UK;Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Kowloon, Hong Kong;Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UK
Venue:
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Year:
2009

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Abstract

In this paper, we consider the robust filtering problem for discrete time-varying systems with delayed sensor measurement subject to norm-bounded parameter uncertainties. The delayed sensor measurement is assumed to be a linear function of a stochastic variable that satisfies the Bernoulli random binary distribution law. An upper bound for the actual covariance of the uncertain stochastic parameter system is derived and used for estimation variance constraints. Such an upper bound is then minimized over the filter parameters for all stochastic sensor delays and admissible deterministic uncertainties. It is shown that the desired filter can be obtained in terms of solutions to two discrete Riccati difference equations of a form suitable for recursive computation in online applications. An illustrative example is presented to show the applicability of the proposed method.