eprintid: 2476
rev_number: 5
eprint_status: archive
userid: 6
dir: disk0/00/00/24/76
datestamp: 2015-01-13 14:24:45
lastmod: 2015-01-13 14:24:45
status_changed: 2015-01-13 14:24:45
type: article
metadata_visibility: show
creators_name: Piga, Dario
creators_name: Tóth, Roland
creators_id: dario.piga@imtlucca.it
creators_id: 
title: A bias-corrected estimator for nonlinear systems with output-error type model structures 
ispublished: pub
subjects: QA75
divisions: CSA
full_text_status: none
keywords: Bias-corrected least-squares estimate; Nonlinear system identification; Output-error models
abstract: 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. 
date: 2014-09
date_type: published
publication: Automatica
volume: 50
number: 9
publisher: Elsevier 
pagerange: 2373 - 2380
id_number: 10.1016/j.automatica.2014.07.021
refereed: TRUE
issn: 0005-1098
official_url: http://www.sciencedirect.com/science/article/pii/S0005109814002969
citation:   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)