State estimation for stochastic discrete-time systems with multiplicative noises and unknown inputs over fading channels

Yueyang Li, Shuai Liu, Maiying Zhong and Steven X. Ding

Applied Mathematics and Computation, 2018, vol. 320, issue C, 116-130

Abstract: This paper deals with robust state estimation problem for a class of stochastic discrete-time systems with multiplicative noises and unknown inputs over fading channels. An unbiased unknown input insensitive filter is designed such that the variance of the estimation error is minimized in the sense of the so-called P-estimation. The filter gain matrix is derived through solving a recursive Riccati equation and a generalized Lyapunov equation. A necessary and sufficient condition that guarantees the existence of the filter is given, which establishes a fundamental limit on the mean square capacity of each fading channel. Unknown input estimation and finite horizon stability of the proposed filter are also discussed. To illustrate the effectiveness of the proposed approach, the proposed algorithm is applied to a faulty remote controlled uninterruptible power system, where both the state and the fault are estimated.

Keywords: Robust estimation; Multiplicative noise; Unknown input; Fading channel; Unbiased minimum-variance filter (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:320:y:2018:i:c:p:116-130

DOI: 10.1016/j.amc.2017.09.008

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