ANALYSIS OF DYNAMIC PROCESS MODELS FOR STRUCTURAL INSIGHT AND MODEL-REDUCTION .1. STRUCTURAL IDENTIFICATION MEASURES

An important consideration in the development of mathematical models f or dynamic simulation, is the identification of the appropriate mathem atical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate an d functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships withi n the process. In this paper, a method is proposed for systematic mode l development for startup and shutdown simulation which is based on th e identification of the essential process structure. The key tool in t his analysis is the method of nonlinear perturbations for structural i dentification and model reduction. Starting from a detailed mathematic al process description both singular and regular structural perturbati ons are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous mo del equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-c hemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations wh ich must be accurately modelled in order to develop a robust plant mod el. The technique generates detailed insight into the dynamic structur e of the models providing a basis for system re-design and dynamic ana lysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd