OPERATING REGIME BASED PROCESS MODELING AND IDENTIFICATION

This paper presents a non-linear modeling framework that supports mode l development in between empirical and mechanistic modeling. A model i s composed of a number of local models valid in different operating re gimes. The local models are combined by smooth interpolation into a co mplete global model. It is illustrated how different kinds of empirica l and mechanistic knowledge and models can be combined with process da ta within this framework. Furthermore, we describe a flexible computer aided modeling tool that supports modeling within this framework. Sim ple but illustrative examples from chemical engineering are used to hi ghlight the flexibility and power of the framework. Copyright (C) 1996 Elsevier Science Ltd