A New Identification Framework for Off-Line Computation of Moving-Horizon Observers

In this technical note, a new nonlinear identification framework is proposed to address the issue of off-line computation of moving-horizon observer estimate. The proposed structure merges the advantages of nonlinear approximators with the efficient computation of constrained quadratic programming p...

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Bibliographic Details
Published in:IEEE transactions on automatic control 2013-07, Vol.58 (7), p.1877-1882
Main Author: Alamir, M.
Format: Article
Language:English
Subjects:
Approximation methods
Automatic
Ecoli
Engineering Sciences
Noise
Noise measurement
nonlinear identification
nonlinear moving-horizon observers
Observers
off-line computation
state estimation
Vectors
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Description
Summary:In this technical note, a new nonlinear identification framework is proposed to address the issue of off-line computation of moving-horizon observer estimate. The proposed structure merges the advantages of nonlinear approximators with the efficient computation of constrained quadratic programming problems. A bound on the estimation error is proposed and the efficiency of the resulting scheme is illustrated using two state estimation examples.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2013.2256016