Abstract
Abstract Petrinets have become a useful tool for modelling various classes of systems, especially those involving parallel computations and concurrent processes. The present paper deals with a method for identification of the Petrinet model from a given set of input-output observations. The method actually involves a modification of the system identification techniques of linear system theory. It has been shown that, by assuming the net to be a discrete-time linear dynamical system, it is possible to arrive at a reduced-order Petrinet model for a dynamical process. This procedure will enable one to obtain a Petrinet model for subsequent analysis systematically, thus bypassing normally used trial-and-error techniques.
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