Simultaneous Input and State Estimation for Linear Time-Varying Continuous-Time Stochastic Systems

Sze Zheng Yong, Minghui Zhu, Emilio Frazzoli

    Research output: Contribution to journalArticle

    4 Scopus citations

    Abstract

    In this technical note, we consider the problem of optimal filtering for linear time-varying continuous-time stochastic systems with unknown inputs. We first show that the unknown inputs cannot be estimated without additional assumptions. Then, we discuss some conditions under which meaningful estimation is possible and propose an optimal filter that simultaneously estimates the states and unknown inputs in an unbiased minimum-variance sense. Conditions for uniform asymptotic stability, and the existence of a steady-state solution, as well as the convergence rate of the state and input estimate biases are given. Moreover, we show that a principle of separation of estimation and control holds and that the unknown inputs may be rejected. A nonlinear vehicle reentry example is given to illustrate that our filter is applicable even when some strong assumptions do not hold.

    Original languageEnglish (US)
    Article number7547940
    Pages (from-to)2531-2538
    Number of pages8
    JournalIEEE Transactions on Automatic Control
    Volume62
    Issue number5
    DOIs
    StatePublished - May 2017

      Fingerprint

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Computer Science Applications
    • Electrical and Electronic Engineering

    Cite this