This paper describes an identification procedure for minimally parametrized multivariable models in the Errors–in–Variables (EIV) context of the Frisch scheme that considers additive white observation noise on the process inputs and outputs. This procedure relies on the geometric approach described in (Guidorzi and Diversi, 2009) that associates EIV models to directions in the noise space. The proposed procedure has been tested by means of a Monte Carlo simulation that confirms its effectiveness.

Frisch scheme-based identification of multivariable errors-in-variables models

DIVERSI, ROBERTO;GUIDORZI, ROBERTO
2009

Abstract

This paper describes an identification procedure for minimally parametrized multivariable models in the Errors–in–Variables (EIV) context of the Frisch scheme that considers additive white observation noise on the process inputs and outputs. This procedure relies on the geometric approach described in (Guidorzi and Diversi, 2009) that associates EIV models to directions in the noise space. The proposed procedure has been tested by means of a Monte Carlo simulation that confirms its effectiveness.
Proceedings of the 15th IFAC Symposium on System Identification
1563
1567
R. Diversi; R. Guidorzi
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/80745
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