Graph transformation as a modelling framework for supervisory control

To make the techniques of supervisory control theory more accessible to non-experts, an intuitive and user-friendly modelling approach is needed to dissociate the modeller from the abstract automaton models used within the theory. This paper attempts to resolve this issue by presenting a modelling framework based upon graph rewriting, in which so-called implicit automaton models are used to generate automata that can be used as input to supervisory synthesis algorithms. It is demonstrated how the proposed modelling approach can be supported by a graph transformation tool such as GROOVE which implements the graph rewriting modelling paradigm.