The use of a semi-rigorous SAG mill model for a hands-on workshop

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dc.contributor.author Bauer, Margret
dc.contributor.author Brooks, Kevin
dc.contributor.author Burchell, John
dc.contributor.author Coetzee, Loutjie
dc.contributor.author Le Roux, Johan Derik
dc.contributor.author McCoy, John
dc.contributor.author Miskin, Jason
dc.contributor.author Winter, Danielle
dc.date.accessioned 2021-07-05T07:55:08Z
dc.date.available 2021-07-05T07:55:08Z
dc.date.issued 2020
dc.description.abstract This paper describes the extension of a grinding mill model that is publicly available for educational and training purposes. This industrially derived model of a mill is used to explain complex concepts of advanced process control (APC) such as model predictive control and soft sensing. The resulting concepts were developed in a hands-on workshop in the wake of the IFAC MMM 2019 conference entitled “Modern Data Analytics for Control in Minerals Processing”. The workshop and the material presented here are aimed at control engineers to explain the use of APC methods to improve process performance. Both academic and industrial control engineers attended the workshop, highlighting the relevance of the application of real-life process control problems. en_ZA
dc.description.department Electrical, Electronic and Computer Engineering en_ZA
dc.description.librarian pm2021 en_ZA
dc.description.uri https://www.journals.elsevier.com/ifac-papersonline en_ZA
dc.identifier.citation Bauer M., Brooks K., Burchell J. et al. 2020, 'The use of a semi-rigorous SAG mill model for a hands-on workshop', IFAC-PapersOnLine, vol. 53, no. 2, pp. 11889-11894. en_ZA
dc.identifier.issn 2405-8963 (online)
dc.identifier.other 10.1016/j.ifacol.2020.12.706
dc.identifier.uri http://hdl.handle.net/2263/80708
dc.language.iso en en_ZA
dc.publisher Elsevier en_ZA
dc.rights © 2020. The Authors. This is an Open Access Article under the CC BY-NC-ND license. en_ZA
dc.subject Control engineering education en_ZA
dc.subject System identification en_ZA
dc.subject Soft sensing en_ZA
dc.subject Multivariate Statistics en_ZA
dc.subject University - industry collaboration en_ZA
dc.subject Advanced process control (APC) en_ZA
dc.title The use of a semi-rigorous SAG mill model for a hands-on workshop en_ZA
dc.type Article en_ZA


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