A nonlinear dynamic process can be described as a composition of several local affine models selected according to the process operating conditions. Such a compound system requires the identification of the local models from data. This work addresses a method for the identification and the optimal selection of the local affine models from a sequence of noisy measurements acquired from the process. The developed technique is applied to the identification of a simulated model.

Nonlinear dynamic system modelling in noisy environment using multiple model approach

SIMANI, Silvio;FANTUZZI, Cesare;ROVATTI, Riccardo;BEGHELLI, Sergio
2000

Abstract

A nonlinear dynamic process can be described as a composition of several local affine models selected according to the process operating conditions. Such a compound system requires the identification of the local models from data. This work addresses a method for the identification and the optimal selection of the local affine models from a sequence of noisy measurements acquired from the process. The developed technique is applied to the identification of a simulated model.
2000
9780780355194
modelling; noise; nonlinear dynamical systems; optimisation; local affine models; local model identification; multiple model approach; nonlinear dynamic system modelling.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1195662
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