This paper addresses the identification of non-linear systems. A wide class of these systems can be described using nonlinear time-invariant regression models, that can be approximated by means of piecewise a ne prototypes with an arbitrary degree of accuracy. This work concerns the identi®cation of piecewise affine model parameters through input-output data affected by additive noise. In order to show the e ectiveness of the developed technique, the results obtained in the identification of both a simple simulated system and a real dynamic process are reported.

Identification of piecewise affine models in noisy environment

FANTUZZI, Cesare
Primo
;
SIMANI, Silvio
Secondo
;
BEGHELLI, Sergio;ROVATTI, Riccardo
2002

Abstract

This paper addresses the identification of non-linear systems. A wide class of these systems can be described using nonlinear time-invariant regression models, that can be approximated by means of piecewise a ne prototypes with an arbitrary degree of accuracy. This work concerns the identi®cation of piecewise affine model parameters through input-output data affected by additive noise. In order to show the e ectiveness of the developed technique, the results obtained in the identification of both a simple simulated system and a real dynamic process are reported.
2002
Fantuzzi, Cesare; Simani, Silvio; Beghelli, Sergio; Rovatti, Riccardo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1209393
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