On the design of a stable adaptive filter for state estimation in high dimensional systems

Authors:
H. S. Hoang;R. Baraille;O. Talagrand
Affiliations:
SHOM/GRGS/CNRS/CNES, 18 Avenue Edouard Belin, 31401 Toulouse, Cédex 4, France;SHOM/GRCS/CMO, 18 Avenue Edouard Belin, 31401 Toulouse, Cédex 4, France;LMD/ENS, 24 Rue Lhomond, 75231 Paris Cédex 05, France
Venue:
Automatica (Journal of IFAC)
Year:
2001

Citing 5
Cited 1

Galerkin approximation of optimal linear filtering of infinite-dimensional linear systems

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Acceleration of stochastic approximation by averaging

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A new reduced-order adaptive filter for state estimation in high-dimensional systems

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Global theory of the Riccati equation

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Estimation of noise covariance matrices for a linear time-varying stochastic process

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Brief paper: On the stability of a reduced-order filter based on dominant singular value decomposition of the system dynamics

Automatica (Journal of IFAC)

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Abstract

Design of specific parametrized gain structures provides a new tool for ensuring stability of reduced-order filter for high-dimensional systems which is optimized adaptively in the minimum prediction error framework.