Methods for automatic control, observation, and optimization in mineral processing plants

Throughput and product quality control for a grinding mill circuit using non-linear MPC

“…Whether to achieve a consistent product quality or throughput, a ROM ore milling circuit is a difficult process to control because of non-linearities, large time delays, unmeasured disturbances, process variables that are difficult to measure, and modelling uncertainties (Coetzee et al, 2010;Hodouin, 2011). Traditionally milling circuits are controlled by decentralized proportional-integral-derivative (PID) controllers (Wei and Craig, 2009b) despite the multivariable nature of the circuits (Pomerleau et al, 2000).…”

“…However, apart from the issue of computational time, the use of model-based controllers in industrial circuits are impeded by the lack of adequate plant measurements to estimate states and parameters for state feedback. Hodouin (2011) describes how the peripheral tools of a control loop are as important as the controller itself to successfully control and optimise a mineral processing plant. The peripheral tools include disturbance observers for external disturbance rejection (Olivier et al, 2012a), model-plant mismatch detection (Olivier and Craig, 2013), and state and parameter estimation (Olivier et al, 2012b).…”

Hardware-in-the-loop simulation platform for supervisory control of mineral grinding process

“…Unfortunately, production practice indicates that the plant still often operates under a non-optimized economic status, thereby producing low quality product in high-energy production. The reason is that "with respect to the economic performance of a MGP plant, the controller performance is most probably not as important as the right selection of the setpoints" [1]. In practice, these loop setpoints are normally regulated by on-site operators.…”

“…As a crucial component of the beneficiation process, mineral grinding process (MGP) is used to grind the run-of-mine ore into suitable particle size such that the valuable mineral constituent can be exposed to be recovered in the subsequent classification process [1,2]. In the past, the process control research of the MGP was focused on the basic loop control methods to ensure the process variables follow their setpoints in a stable operation.…”

Dual particle filters for state and parameter estimation with application to a run-of-mine ore mill

“…Mineral processing operations are generally difficult to control owing to the presence of strong external disturbances, poor process models and process variables that are difficult to measure [1]. Run-of-mine (ROM) ore milling is an example of such a process, as grinding ore down to a fine product is usually the first step in any metallurgical extraction process [2].…”