A geometric approach to multivariable errors-in-variables identification

The extension of the Frisch scheme from the original algebraic case to the dynamic one leads to the use of errors–in–variablesmodels where the measurements of the input and output are affected by additive white and independent noises. This problem admits a single solution when the assumptions of the scheme are exactly fulfilled but its application to real processes requires the introduction of specific model selection criteria. This paper analyzes the additional problems encountered in the extension of Frisch identification to the multivariable case and introduces a geometric approach for its solution.