A new identification framework for off-Line computation of moving-horizon observers
M Alamir - IEEE Transactions on Automatic Control, 2013 - ieeexplore.ieee.org
IEEE Transactions on Automatic Control, 2013•ieeexplore.ieee.org
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.
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.
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.
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