Abstract
This paper concerns the identification of multivariable errors-in-variables (EIV) models, i.e. models where all inputs and outputs are assumed as affected by additive errors. The identification of MIMO EIV models introduces challenges not present in SISO and MISO cases. The approach proposed in the paper is based on the extension of the dynamic Frisch scheme to the MIMO case. In particular, the described identification procedure relies on the association of EIV models with directions in the noise space and on the properties of a set of high order Yule–Walker equations. A method for estimating the system structure is also described.
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