Recursive system identification in the presence of noise and model uncertainties

Er-Wei Bai; Roberto Tempo; Krishan Nagpal

doi:10.1016/S0167-6911(97)00057-1

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Recursive system identification in the presence of noise and model uncertainties

Journal article

Peer reviewed

Recursive system identification in the presence of noise and model uncertainties

Er-Wei Bai, Roberto Tempo and Krishan Nagpal

Systems & control letters, Vol.32(1), pp.57-62

1997

DOI: 10.1016/S0167-6911(97)00057-1

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Abstract

The main contribution of this paper is a recursive algorithm for parametric system identification in the presence of both noise and model uncertainties. The estimates provided by this algorithm are not invalidated, after a learning period, by the observed input-output data and the assumed system and uncertainty structures. A complementary off-line algorithm derived from the on-line algorithm is also presented.

Parametric system identification

Recursive algorithms

Noise

Model uncertainties

Details

Title: Subtitle: Recursive system identification in the presence of noise and model uncertainties
Creators: Er-Wei Bai - Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, USA
Roberto Tempo - CENS-CNR, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Krishan Nagpal - Scientific Systems Co. Inc., 500 W. Cummings Park, Woburn, MA 01801, USA
Resource Type: Journal article
Publication Details: Systems & control letters, Vol.32(1), pp.57-62
Publisher: Elsevier B.V
DOI: 10.1016/S0167-6911(97)00057-1
ISSN: 0167-6911
eISSN: 1872-7956
Language: English
Date published: 1997
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984083848602771

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