Reduced Order Modeling for Glass Manufacturing Process

Satyajit K. Wattamwar, Dr. Siep Weiland, Prof. A.C.P.M. Backx
TU Einhoven

Industrial Glass Manufacturing Process (IGMP) is one of the complex, multiphase, distributed parameter systems. It inherently includes various physiochemical effects with a large variation in process time constants. This is further accompanied by very limited in-situ information available in the form of few temperature and level sensors. The increasing demand for flexible process operation, pressing need for improving the quality, increasing energy costs and increasing environmental regulations motivates one to automate the glass manufacturing process. Modern process automation can guarantee improved performance and reduced wastage of raw material under uncertainties in the process operation. It eliminates the need for heuristic, old fashioned tuning of process PID controller which can no longer be used for increased demand from novel types of glass and its production processes. Control of such challenging process operation needs advanced automatic control which is possible only by Rigorous Model Predictive Controllers (RMPC).

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