The identification of dynamic processes can be performed by means of different classes of models relying on different stochastic environments to describe the misfit between the model and process observations. This paper introduces a new class of models by considering additive error terms on the observations of the input and output of ARARX models and proposes a three–step identification procedure for their identification. ARARX + noise models extend the traditional ARARX or ARMAX ones and can be seen as errors–in–variables models where both measurement errors and process disturbances are taken into account. The results of Monte Carlo simulations show the good performance of the proposed identification procedure.

R. Diversi, R. Guidorzi, U. Soverini (2008). Identification of ARARX models in presence of additive noise. s.l : International Federation of Automatic Control.

Identification of ARARX models in presence of additive noise

DIVERSI, ROBERTO;GUIDORZI, ROBERTO;SOVERINI, UMBERTO
2008

Abstract

The identification of dynamic processes can be performed by means of different classes of models relying on different stochastic environments to describe the misfit between the model and process observations. This paper introduces a new class of models by considering additive error terms on the observations of the input and output of ARARX models and proposes a three–step identification procedure for their identification. ARARX + noise models extend the traditional ARARX or ARMAX ones and can be seen as errors–in–variables models where both measurement errors and process disturbances are taken into account. The results of Monte Carlo simulations show the good performance of the proposed identification procedure.
2008
Proceedings of the 17th IFAC World Congress
432
437
R. Diversi, R. Guidorzi, U. Soverini (2008). Identification of ARARX models in presence of additive noise. s.l : International Federation of Automatic Control.
R. Diversi; R. Guidorzi; U. Soverini
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/64693
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