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)

## 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.

Item Type: | Article |
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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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