This paper addresses the identification of non–linear dynamic systems. A wide class of these systems can be described using nonlinear 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 inputoutput data acquired from a dynamic process. In order to show the effectiveness of the developed technique, when exploited also for FDI purpose, the results obtained in the identification of both a simple simulated system and a real dynamic process are reported.
PWA Dynamic Identification for Nonlinear Model Fault Detection / S., Simani; Fantuzzi, Cesare. - ELETTRONICO. - (2006), pp. 1121-1126. (Intervento presentato al convegno 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes tenutosi a Beijing, China nel 29 August -- 1 September 2006) [10.3182/20060829-4-cn-2909.00187].
PWA Dynamic Identification for Nonlinear Model Fault Detection
FANTUZZI, Cesare
2006
Abstract
This paper addresses the identification of non–linear dynamic systems. A wide class of these systems can be described using nonlinear 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 inputoutput data acquired from a dynamic process. In order to show the effectiveness of the developed technique, when exploited also for FDI purpose, the results obtained in the identification of both a simple simulated system and a real dynamic process are reported.
Pubblicazioni consigliate
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris
