Abstract
This article discusses a new modular design approach for hybrid models consisting of a dynamic framework augmented with static fuzzy sub-models. As the framework is physically based, the models have a dynamic behaviour that corresponds well with the original process. Their fit to process data assures good steady state behaviour and corrects the dynamic behaviour for assumptions and simplifications. The hybrid model design is illustrated for three dynamically different processes: an ideally mixed, a distributed and a chained process.
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