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Real-Time Updating of a Dynamic Fundamental Model for Froth Flotation Process Open Access


Other title
Dynamic Modelling
Extended Kalman Filter
Froth Flotation
Type of item
Degree grantor
University of Alberta
Author or creator
Sekhavat, Masih
Supervisor and department
Dubljevic, Stevan (Chemical and Materials Engineering)
Prasad, Vinay (Chemical and Materials Engineering)
Examining committee member and department
Huang, Biao (Chemical and Materials Engineering)
Department of Chemical and Materials Engineering
Process Control
Date accepted
Graduation date
Master of Science
Degree level
Froth flotation is one of the most common methods in the mineral industry for selective extraction of a small fraction of desired mineral from a finely mixed ground ore. This work explores the development of a fundamental dynamic model for froth flotation with parameters of the model being estimated and updated online with applicable techniques such as extended Kalman filtering. In the first step, a fundamental dynamic model was proposed and then a series of flotation experiments in a JK Tech batch flotation cell were designed and performed by the Fractional Factorial Design method. In the second step, the developed model was reconciled with dynamic data from the batch flotation cell, and model parameters were estimated and updated on-line using extended Kalman filtering. Results show the applicability of the Kalman filter estimator for tracking changes in operational conditions and in parameter estimation when disturbances were applied to the system.
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