Design and implementation of a knowledge-based framework for the modelling and simulation of hybrid systems

The paper describes a knowledge-based framework for the modelling and simulation of hybrid systems and its implementation in the G2 Expert System tool. The approach is based on three key notions : a hybrid model base, hybrid simulation, and interactions between dissimilar model elements. The hybrid model base is a repository of model building paradigms, including Grafcets, equations, rules, and object-orientation. Hybrid simulation is based on the concurrent execution of the G2 continuous simulator, a Grafcet simulator, and the G2 inference engine. The three simulators exchange information through interactions which are dynamically created during a simulation. Interactions are modelled as notional objects with attributes specifying the variables and variable types involved in the exchange of information. This represents a form of causality between the source and receptor variables. The approach is illustrated by applying it to the modelling and simulation of a rolling mill.