Operating regime based process modeling and identification

This paper presents a non-linear modeling framework that supports model development in between empirical and mechanistic modeling. A model is composed of a number of local models valid in different operating regimes. The local models are combined by smooth interpolation into a complete global model. It is illustrated how different kinds of empirical and mechanistic knowledge and models can be combined with process data within this framework. Furthermore, we describe a flexible computer aided modeling tool that supports modeling within this framework. Simple but illustrative examples from chemical engineering are used to highlight the flexibility and power of the framework. Copyright (C) 1996 Elsevier Science Ltd