In many practical situations the process data are affected by noise on both inputs and outputs. In these contexts, errors–in–variables (EIV) models can be the best choice for identification purposes and several approaches based on these representation are present in the literature. This work refers to one of these methods, the so–called dynamic Frisch scheme. In particular, two different Frisch scheme–based algorithms are analyzed and compared by means of Monte Carlo simulations.
Frisch scheme-based algorithms for EIV identification
DIVERSI, ROBERTO;GUIDORZI, ROBERTO;SOVERINI, UMBERTO
2004
Abstract
In many practical situations the process data are affected by noise on both inputs and outputs. In these contexts, errors–in–variables (EIV) models can be the best choice for identification purposes and several approaches based on these representation are present in the literature. This work refers to one of these methods, the so–called dynamic Frisch scheme. In particular, two different Frisch scheme–based algorithms are analyzed and compared by means of Monte Carlo simulations.File in questo prodotto:
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