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A dynamic flotation model for real-time control and optimisation
Thesis (PhD (Electronic Engineering))--University of Pretoria, 2023.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2023
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| _version_ | 1867613536357711872 |
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| access_status_str | Open Access |
| author2 | Craig, Ian K. |
| author_browse | Craig, Ian K. |
| author_facet | Craig, Ian K. |
| collection | Thesis |
| dc_rights_str_mv | © 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Thesis (PhD (Electronic Engineering))--University of Pretoria, 2023. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/89946 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:37:42.457Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/89946 A dynamic flotation model for real-time control and optimisation Craig, Ian K. djoosthuizen02@gmail.com Le Roux, Johan Derik Oosthuizen, Daniël Jacobus UCTD Model predictive control Modelling Moving horizon estimator Observability Optimisation Process control Process optimisation Simulation State and parameter estimation Flotation Thesis (PhD (Electronic Engineering))--University of Pretoria, 2023. Froth flotation models that are developed for circuit design applications are often not suitable for model-based dynamic control and optimisation applications. For real-time control and optimisation applications dynamic models of the key flotation mechanisms are required, as these use real-time measurements to update internal model states and estimate model parameters in real-time. The development of a dynamic froth flotation model is described, based on a combination of fundamental mass and volume balances, fundamental steady-state froth models and empirical models for bubble size and air recovery. The model outputs are defined to correspond with real-time measurements that are commonly available on industrial flotation circuits, including measurements from froth imaging devices in combination with measurements of levels, flow rates, densities and grades. The flotation model is analysed for state observability and controllability, and it is shown that the model states and parameters can be estimated from real-time process measurements that are commonly available on industrial flotation circuits. The ability to estimate process parameters in real-time opens up opportunities for improved process control and optimisation by compensating for a specific flotation mechanism rather than the combined effect of multiple flotation mechanisms. The speed of response can also be improved when more accurate models are maintained by continuously updating model parameters. The flotation model, a state and a parameter estimator and model predictive controller are combined to simulate the potential benefits of using a non-linear model-based approach with state and parameter estimation capabilities in a dynamic control and optimisation application on flotation circuits. The strategy is shown to reject typical process disturbances effectively in the presence of process noise and outperforms a linear non-model based control strategy by a significant margin. Electrical, Electronic and Computer Engineering PhD (Electronic Engineering) Unrestricted 2023-03-03T06:11:41Z 2023-03-03T06:11:41Z 2023-05-12 2023 Thesis * A2023 https://repository.up.ac.za/handle/2263/89946 https://doi.org/10.25403/UPresearchdata.22197514.v1 en © 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Model predictive control Modelling Moving horizon estimator Observability Optimisation Process control Process optimisation Simulation State and parameter estimation Flotation A dynamic flotation model for real-time control and optimisation |
| title | A dynamic flotation model for real-time control and optimisation |
| title_full | A dynamic flotation model for real-time control and optimisation |
| title_fullStr | A dynamic flotation model for real-time control and optimisation |
| title_full_unstemmed | A dynamic flotation model for real-time control and optimisation |
| title_short | A dynamic flotation model for real-time control and optimisation |
| title_sort | dynamic flotation model for real time control and optimisation |
| topic | UCTD Model predictive control Modelling Moving horizon estimator Observability Optimisation Process control Process optimisation Simulation State and parameter estimation Flotation |
| url | https://repository.up.ac.za/handle/2263/89946 https://doi.org/10.25403/UPresearchdata.22197514.v1 |