Model reduction for dynamic optimization of chemical processes

Project members: J. van den Berg, O.H. Bosgra

Sponsored by: GROWTH Program of the European Union

Process industry has become more market driven. Nowadays, e.g. in the polymer industry customers require between 30-100 varieties of product grades due to wide variety of costumer products. The grades have to be produced within tight specifications and against competitive price using an increasing variation in input quality of feedstock material. Difficulties of production units to adapt to this demand lead to unnecessary resource usage waste production, energy usage and higher cost.

Current control and optimization systems do not support the dynamic non-linear process behavior of production plants. They cannot use dynamic process models (too complex) and no adequate algorithms exist. INCOOP is aiming at fully integrated dynamic and non-linear process control and optimization.

The contribution of this research is the assessment of existing and development of new model reduction techniques that exploit the available first principle models and reduce the computational load for the optimization.