Title :
Nonlinear MPC and inferential sensing for PVC production
Author :
Havlena, V. ; Barva, P.
Author_Institution :
Honeywell Technol. Center Europe, Prague, Czech Republic
Abstract :
A nonlinear model-based predictive controller with new features including range control, multirate sampling and two degrees of freedom control for PVC batch control/optimization is introduced. The lumped uncertainty design of the semi-empirical batch model based on data-mining technologies is described. The controller is complemented by an inferential sensor to reduce the uncertainty about the reactivity of the batch. The knowledge of reactivity is used for batch time optimization under constraints given by shared cooling resources of the plant
Keywords :
batch processing (industrial); data mining; nonlinear control systems; optimal control; optimisation; polymerisation; predictive control; process control; PVC production; batch control; batch time optimization; data-mining technologies; inferential sensing; lumped uncertainty design; multirate sampling; nonlinear MPC; nonlinear model-based predictive controller; range control; reactivity; semi-empirical batch model; shared cooling resources; two degrees of freedom control; Automatic control; Control systems; Cooling; Inductors; Polymers; Predictive models; Production; Sampling methods; Temperature control; Uncertainty;
Conference_Titel :
Control Applications, 1999. Proceedings of the 1999 IEEE International Conference on
Conference_Location :
Kohala Coast, HI
Print_ISBN :
0-7803-5446-X
DOI :
10.1109/CCA.1999.800918
