Identification of piecewise affine models in noisy environment

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.