Stepwise identification of automated discrete manufacturing systems

This paper deals with the identification of discrete event systems that are automated through a programmable logic controller (PLC). The behavior of the closed loop system (PLC and Plant) is observed during its operation and is represented by a single long sequence of input/output vectors. The proposed method allows building stepwise an interpreted Petri net model, which is updated when new behavior is observed. The identification strategy is composed of several polynomial time algorithms implemented in a software tool that creates and draws the IPN model.