This paper deals with the identification of multi–input multi–output errors–in–variables (EIV) models in the Frisch scheme context. The extension of the Frisch scheme to MIMO models introduces some problems not present in the SISO case. The approach proposed in this paper relies on the association of EIV models to directions in the noise space and on the statistical properties of the residual of the EIV model. In particular, a selection criterion based on the comparison of the theoretical statistical properties of the residual with those computed from the data is introduced. The performance of the proposed identification algorithm is evaluated by means of numerical simulations.

A covariance–matching criterion in the Frisch scheme identification of MIMO EIV models

DIVERSI, ROBERTO;GUIDORZI, ROBERTO
2012

Abstract

This paper deals with the identification of multi–input multi–output errors–in–variables (EIV) models in the Frisch scheme context. The extension of the Frisch scheme to MIMO models introduces some problems not present in the SISO case. The approach proposed in this paper relies on the association of EIV models to directions in the noise space and on the statistical properties of the residual of the EIV model. In particular, a selection criterion based on the comparison of the theoretical statistical properties of the residual with those computed from the data is introduced. The performance of the proposed identification algorithm is evaluated by means of numerical simulations.
Proceedings of the 16th IFAC Symposium on System Identification
1647
1652
R. Diversi; R. Guidorzi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/128172
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