Identification, modelling, and adaptive control of an aluminium reduction cell

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dc.contributor.authorMcKenna, Joan S.
dc.date.accessioned2012-05-08T12:25:05Z
dc.date.accessioned2023-04-21T04:20:18Z
dc.date.available2012-05-08T12:25:05Z
dc.date.available2023-04-21T04:20:18Z
dc.date.issued1991-05-08
dc.descriptionA thesis submitted to the Board of Postgraduate Studies, Kwame Nkrumah University of Science and Technology, Kumasi, in partial fulfilment of the requirements for the award of the Degree of Master of Philosophy in Chemical Engineering, 1991en_US
dc.description.abstractThe estimation of the alumina concentration in the bath of aluminium reduction cells is a difficult task due to harsh operating conditions within the cells, the complexity of the process, and noise corrupted data. Knowledge of the concentration could significantly improve production efficiency and could be used to enhance the feed control system. In this report, an alumina concentration estimator is developed for a 140 kA prebake aluminium reduction cell. The estimation programme uses experimentally determined models of alumina concentration as a function of time and ohmic resistance as a function of alumina concentration in an extended Kalman filter algorithm with a feedback variable of ohmic resistance. The estimator was tested successfully on simulated and measured cell data. It is shown how the estimator could be incorporated into a feed control algorithm and the control strategy is applied to real and simulated input data.en_US
dc.description.sponsorshipKNUSTen_US
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/3714
dc.language.isoenen_US
dc.relation.ispartofseries1832;
dc.titleIdentification, modelling, and adaptive control of an aluminium reduction cellen_US
dc.typeThesisen_US
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