DocumentCode
706489
Title
Identification of multivariable errors-in-variables models
Author
Castaldi, P. ; Diversi, R. ; Guidorzi, R. ; Soverini, U.
Author_Institution
Dipt. di Elettron., Inf. e Sist., Univ. di Bologna, Bologna, Italy
fYear
1999
fDate
Aug. 31 1999-Sept. 3 1999
Firstpage
969
Lastpage
974
Abstract
The paper deals with a new identification approach, based on a prediction error method, for multivariable errors-in-variables models (EIV). Starting from the ARMAX decomposition of MIMO EIV processes and congruence conditions between noisy sequences and the constraints of EIV representations, the simultaneous estimate of the model parameters and of the noise covariance matrices is obtained. Numerical simulations are included to illustrate the effectiveness of the proposed algorithm.
Keywords
MIMO systems; autoregressive moving average processes; parameter estimation; ARMAX decomposition; MIMO EIV processes; congruence conditions; multivariable errors-in-variables model identification; noise covariance matrices; noisy sequences; prediction error method; Computational modeling; Covariance matrices; MIMO; Noise; Noise measurement; Numerical models; Predictive models; System Identification; errors-in-variables models; multivariable models; optimal ARMAX predictor;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (ECC), 1999 European
Conference_Location
Karlsruhe
Print_ISBN
978-3-9524173-5-5
Type
conf
Filename
7099433
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