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A bias-corrected estimator for nonlinear systems with output-error type model structures

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)

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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.

Item Type: Article
Identification Number: 10.1016/j.automatica.2014.07.021
Uncontrolled Keywords: Bias-corrected least-squares estimate; Nonlinear system identification; Output-error models
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Research Area: Computer Science and Applications
Depositing User: Ms T. Iannizzi
Date Deposited: 13 Jan 2015 14:24
Last Modified: 13 Jan 2015 14:24
URI: http://eprints.imtlucca.it/id/eprint/2476

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