A unified filter for simultaneous input and state estimation of linear discrete-time stochastic systems

Sze Zheng Yong, Minghui Zhu, Emilio Frazzoli

    Research output: Contribution to journalArticle

    68 Scopus citations

    Abstract

    In this paper, we present a unified optimal and exponentially stable filter for linear discrete-time stochastic systems that simultaneously estimates the states and unknown inputs in an unbiased minimum-variance sense, without making any assumptions on the direct feedthrough matrix. We also provide the connection between the stability of the estimator and a system property known as strong detectability, and discuss the global optimality of the proposed filter. Finally, an illustrative example is given to demonstrate the performance of the unified unbiased minimum-variance filter.

    Original languageEnglish (US)
    Pages (from-to)321-329
    Number of pages9
    JournalAutomatica
    Volume63
    DOIs
    StatePublished - Jan 1 2016

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Electrical and Electronic Engineering

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