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

Abstract

In this paper, 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.

arXiv commentTo Appear in IEEE Transactions on Automatic Control (This version is the second revision)