This paper addresses the identification of non-linear dynamic systems. A wide class of these systems can be described using non-linear time-invariant regression models, that can be approximated by means of piecewise affine prototypes with an arbitrary degree of accuracy. This work concerns the identification of piecewise affine model structure through input-output data acquired from a dynamic process. In order to show the effectiveness of the developed technique, the results obtained in the identification of both a simple simulated system and a real dynamic process are reported.
Parameter identification of piecewise affine dynamic models from input-output data / Simani, S.; Beghelli, S.; Fantuzzi, C.; Rovatti, R.. - 36:6(2003), pp. 21-26. (Intervento presentato al convegno 2003 IFAC Conference on Analysis and Design of Hybrid Systems, ADHS 2003 tenutosi a fra nel 2003) [10.1016/S1474-6670(17)36401-7].
Parameter identification of piecewise affine dynamic models from input-output data
Simani S.;Beghelli S.;Fantuzzi C.;
2003
Abstract
This paper addresses the identification of non-linear dynamic systems. A wide class of these systems can be described using non-linear time-invariant regression models, that can be approximated by means of piecewise affine prototypes with an arbitrary degree of accuracy. This work concerns the identification of piecewise affine model structure through input-output data acquired from a dynamic process. In order to show the effectiveness of the developed technique, the results obtained in the identification of both a simple simulated system and a real dynamic process are reported.Pubblicazioni consigliate
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