This thesis deals with the implementation of a state estimation technique (EKF, Extended Kalman Filter) on a preexisting dynamic model of a steam cracker (PDAE, 227 differential variables, 14268 algebraic variables), using the dynamic process simulator gPROMS. Given few and reliable on-line measurements coming from the real plant, the estimator is able to predict the state of coking of the furnace by adapting the model prediction with the availble measurements
State estimation techniques for on-line model adaptation: a case study in thermal cracking
Bano, Gabriele
2015/2016
Abstract
This thesis deals with the implementation of a state estimation technique (EKF, Extended Kalman Filter) on a preexisting dynamic model of a steam cracker (PDAE, 227 differential variables, 14268 algebraic variables), using the dynamic process simulator gPROMS. Given few and reliable on-line measurements coming from the real plant, the estimator is able to predict the state of coking of the furnace by adapting the model prediction with the availble measurementsFile in questo prodotto:
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Utilizza questo identificativo per citare o creare un link a questo documento:
https://hdl.handle.net/20.500.12608/19970