Identification of the unobservable behaviour of industrial automation systems by Petri nets

This paper addresses the problem of identifying the model of the unobservable behaviour of discrete event systems in the industrial automation sector. Assuming that the fault-free system structure and dynamics are known, the paper proposes an algorithm that monitors the system on-line, storing the occurred observable event sequence and the corresponding reached states. At each event observation, the algorithm checks whether some unobservable events have occurred on the basis of the knowledge of the Petri net (PN) modelling the nominal system behaviour and the knowledge of the current PN marking. By defining and solving some integer linear programming problems, the algorithm decides whether it is necessary to introduce some unobservable (silent) transitions in the PN model and provides a PN structure that is consistent with the observed event string. A case study describing an industrial automation system shows the efficiency and the applicability of the proposed algorithm.

Research Highlights
► A real time algorithm is developed for identifying a Petri net model of the unobservable behaviour of discrete event systems.
► At each event observation the algorithm defines and solves some integer linear programming problems.
► The algorithm provides in a recursive way a Petri net model that is consistent with the observed dynamics.
► The identification approach does not require the knowledge of the unobservable behaviour and weak assumptions on the faulty behaviour are required.
► A case study describing an industrial automation system shows the technique efficiency and applicability.