EKF based State Estimation in a CFI Copolymerization Reactor including Polymer Quality Information

Tamagnini, Filippo (2020) EKF based State Estimation in a CFI Copolymerization Reactor including Polymer Quality Information. [Laurea magistrale], Università di Bologna, Corso di Studio in Ingegneria chimica e di processo [LM-DM270]
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State estimation is an integral part of modern control techniques, as it allows to characterize the state information of complex plants based on a limited number of measurements and the knowledge of the process model. The benefit is twofold: on one hand it has the potential to rationalize the number of measurements required to monitor the plant, thus reducing costs, on the other hand it enables to extract information about variables that have an effect on the system but would otherwise be inaccessible to direct measurement. The scope of this thesis is to design a state estimator for a tubular copolymerization reactor, with the aim to provide the full state information of the plant and to characterize the quality of the product. Due to the fact that, with the existing set of measurements, only a small number of state variables can be observed, a new differential pressure sensor is installed in the plant to provide the missing information, and a model for the pressure measurement is developed. Following, the state estimation problem is approached rigorously and a comprehensive method for analyzing, tuning and implementing the state estimator is assembled from scientific literature, using a variety of tools from graph theory, linear observability theory and matrix algebra. Data reduction and visualization techniques are also employed to make sense of high dimensional information. The proposed method is then tested in simulations to assess the effect of the tuning parameters and measured set on the estimator performance during initialization and in case of estimation with plant-model mismatch. Finally, the state estimator is tested with plant data.

Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Tamagnini, Filippo
Relatore della tesi
Correlatore della tesi
Corso di studio
Ingegneria di processo
Ordinamento Cds
Parole chiave
Extended Kalman Filter,EKF,State estimation,Advanced control,state observer,copolymerization,observability,continuous process,chemical engineering,process automation,model predictive control,process control,state space,state information,soft sensor,coiled flow inverter,method of moments
Data di discussione della Tesi
13 Marzo 2020

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