relation: http://eprints.imtlucca.it/2476/
title: A bias-corrected estimator for nonlinear systems with output-error type model structures 
creator: Piga, Dario
creator: Tóth, Roland
subject: QA75 Electronic computers. Computer science
description: Abstract Parametric identification of linear time-invariant (LTI) systems with output-error (OE) type of noise model structures has a well-established theoretical framework. Different algorithms, like instrumental-variables based approaches or prediction error methods (PEMs), have been proposed in the literature to compute a consistent parameter estimate for linear {OE} systems. Although the prediction error method provides a consistent parameter estimate also for nonlinear output-error (NOE) systems, it requires to compute the solution of a nonconvex optimization problem. Therefore, an accurate initialization of the numerical optimization algorithms is required, otherwise they may get stuck in a local minimum and, as a consequence, the computed estimate of the system might not be accurate. In this paper, we propose an approach to obtain, in a computationally efficient fashion, a consistent parameter estimate for output-error systems with polynomial nonlinearities. The performance of the method is demonstrated through a simulation example. 
publisher: Elsevier 
date: 2014-09
type: Article
type: PeerReviewed
identifier:   Piga, Dario and Tóth, Roland  A bias-corrected estimator for nonlinear systems with output-error type model structures.  Automatica, 50 (9).  2373 - 2380.  ISSN 0005-1098      (2014)  
relation: http://www.sciencedirect.com/science/article/pii/S0005109814002969
relation: 10.1016/j.automatica.2014.07.021