Real time identification of discrete event systems by Petri Nets

The paper defines the identification problem for discrete event systems as the problem of inferring a Petri Net (PN) model using the observation of the events and the available output vectors. The transition and place sets are assumed unknown and only an upper bound of the number of places is given. Hence, the identification problem is solved by an algorithm that stores in real-time the occurred events and the corresponding output vectors. An integer linear programming problem is defined and solved at each observation so that the PN system can be recursively identified. An example shows the flexibility and simplicity of the proposed technique