On the current state of flotation modelling for process control

D. J. Oosthuizen, I. K. Craig, S. L. Jämsä-Jounela, B. Sun

Research output: Contribution to journalConference articleScientificpeer-review

15 Citations (Scopus)
124 Downloads (Pure)


Despite significant effort in modelling and simulating flotation circuits, comprehensive model based control and optimisation implementations on industrial circuits remain scarce. In this paper, the factors preventing more widespread implementation of model-based control and optimisation applications are investigated by focussing on three aspects. Firstly, the critical variables required in a simplified flotation model are identified. Models that are currently used in control, optimisation and supervisory applications are thereafter analysed to determine to what extent the required variables are modelled. Finally, online instrumentation available to support these models are investigated, also including instrumentation that is still under development and not commonly available in commercial applications. Although models used in control applications tend to focus on subsections of the flotation process, there seem to be a good agreement between the required and modelled variables. Model fitting however often relies on extensive sampling campaigns that will need to be repeated regularly to maintain model accuracy. A number of online measurements of sufficient accuracy are still not available to support these models, compromising the long term reliable use of models in online applications. The fact that flotation processes are in many instances not extensively instrumented, constrains online maintenance and adaption of model based solutions further.

Original languageEnglish
Pages (from-to)19-24
Number of pages6
Issue number2
Publication statusPublished - 1 Dec 2017
MoE publication typeA4 Article in a conference publication
EventControl Conference Africa - University of Pretoria , Johannesburg, South Africa
Duration: 7 Dec 20178 Dec 2017


  • Flotation modelling
  • identification
  • model based control
  • optimisation
  • process control


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