Approximation of Nonlinear Systems with Identified Hybrid Models

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, 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.