Multivariable output–error identification does not constitute, in any way, a straightforward extension of the scalar case. The aim of this paper is twofold: 1) Introduction of a new minimal parametrization for multivariable output error models leading to an easily implementable prediction error identification procedure; 2) Comparison of PEM and errors–in–variables approaches based on the dynamic Frisch scheme in the identification of MIMO output error processes.
R. Guidorzi, R. Diversi (2011). On the use of minimal parametrizations in multivariable output-error identification. s.l : IEEE [10.1109/MED.2011.5983060].
On the use of minimal parametrizations in multivariable output-error identification
GUIDORZI, ROBERTO;DIVERSI, ROBERTO
2011
Abstract
Multivariable output–error identification does not constitute, in any way, a straightforward extension of the scalar case. The aim of this paper is twofold: 1) Introduction of a new minimal parametrization for multivariable output error models leading to an easily implementable prediction error identification procedure; 2) Comparison of PEM and errors–in–variables approaches based on the dynamic Frisch scheme in the identification of MIMO output error processes.File in questo prodotto:
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