Optimal Control of Column Flotation Process using Dynamic Fundamental Models

• Author / Creator

  Azhin, Maryam

• Column flotation, as a selective separation process based on differences in surface properties, is used for a broad range of applications in the mineral processing industry, including metallic, non-metallic, and coal ores, as well as wastewater treatment over the last fifty years. Flotation is a commonly used method for the separation of valuable minerals (metals) from gangue. Application of flotation columns is dominant in Australia, the USA, and China, while in North America the use of flotation column has declined significantly. The reason for this decline is that still many unanswered questions exist regarding flotation column operational performance. Operational performance is related to having control over the system in order to keep the
  system in the preferable operational region to reach desired product grades and/or recovery and/or performance objectives while ensuring the stability of the hydrodynamic system.
  Moreover, available industrial flotation technology is effective over a size range of approximately 15 to 150 microns. The above consideration provides a strong motivation for the development of a hybrid column geometry to extend the refining range from very fine to very coarse particles by adding a mixer to the geometry of the flotation column. The main goal of this thesis is on-line model-based monitoring and control of the hybrid flotation column system. In this regard, optimal controller (OC) design, as the ideal solutions for high-quality control, which explicitly accounts for optimality and stability is applied. Although OC has been successfully implemented in many processes, so far the common control approach in flotation plants is knowledge-based (fuzzy logic, supervisory, and PID). This research addresses the question of how the state-of-the-art column flotation control realization is close to successful application of advanced OC. In particular, it is demonstrated that the limits of the application of OC are specific difficulties in having reliable dynamic models, state estimation, controller design and having good measurements. For the purpose of designing a controller the following goals have been achieved, 1) a three-phase continuous hybrid flotation column that seeks to obtain the benefits of both mechanical cells and flotation columns is modelled as the interconnection of a CSTR representing the well-mixed zone and two plug-flow reactors (PFR) representing pulp and froth zones. The dynamic plant model representation of the novel flotation column accounts for both dynamic variations and micro-scale processes such as bubble-particle collision and attachment, and the appearance and breakage of bubbles. This complex distributed parameter system (DPS) is described by sets of nonlinear coupled conservation counter-current hyperbolic partial differential equations (PDEs) and one set of ordinary differential equations (ODEs). 2) The dynamic conservation law based model for the continuous hybrid flotation column is utilized in an optimal model-based controller design. The stability of the system is ensured (i.e. the controller does not make the system unstable), in addition, this modern state-of-the-art controller synthesis accounts for optimality and performance.
  The controller design utilizes a linear model obtained by linearization at operating steady states of interest. A full-state optimal feedback control law is designed and controller performance has been demonstrated through a numerical simulation of physically meaningful and relevant plant operating conditions. The LQR-based optimal controller outperforms PI-based control in terms of a return to steady state after a perturbation in the initial condition, 3) model-based state estimators and observers are explored. This was due to the fact that in practice some essential properties for the monitoring and control purposes cannot be measured directly (for example, the amount of metal extracted from ore at the column exit); instead, they must be estimated from available measurements.
  Finally, the proposed model and real-time state estimation is validated using realtime measurements based on experimental data.

• Subjects / Keywords

  • Column Flotation
  • Dynamic 3Phase Modelling
  • Optimal Control
  • Estimation

• Graduation date

  Fall 2020

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/r3-cwrm-v853

• License

  Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.