A survey of grinding circuit control methods: from decentralized PID controllers to multivariable predictive controllers

Pomerleau, A.; Hodouin, D.; Desbiens, André; Gagnon, Éric

doi:10.1016/s0032-5910(99)00207-7

Cited by 96 publications

(44 citation statements)

References 6 publications

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“…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). Significant improvement in product quality, throughput and power consumption is possible through multivariable control techniques.…”

Section: Control Of Grinding Mill Circuitsmentioning

confidence: 99%

“…The use of model-based controllers is preferred over traditional PID controllers for grinding mill circuits (Niemi et al, 1997;Pomerleau et al, 2000;Ramasamy et al, 2005). 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.…”

Section: State Estimationmentioning

confidence: 99%

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

Roux

Olivier

Naidoo

et al. 2016

Journal of Process Control

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A non-linear model-based control architecture for a single-stage grinding mill circuit closed with a hydrocyclone is proposed. The control architecture aims to achieve independent control of circuit throughput and product quality, and consists of a non-linear model predictive controller for grinding mill circuit control, and a dynamic inversion controller to control the fast sump dynamics. A particle filter is used to estimate the mill states, and an algebraic routine is used to estimate the sump states. The observers make use of real-time continuous measurements commonly available on industrial plants. Simulation results show that control objectives can be achieved by the controller despite the presence of measurement noise and disturbances.

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Section: Control Of Grinding Mill Circuitsmentioning

confidence: 99%

Section: State Estimationmentioning

confidence: 99%

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

Roux

Olivier

Naidoo

et al. 2016

Journal of Process Control

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“…Until now, there have been some attempts on solving this supervisory control problem. These begin with some model-based control and optimization methods, such as real-time optimization (RTO) [25], model predictive control (MPC) [2,[26][27][28] and adaptive decoupled control [29,30]. But, these methods are hard to be applied in practical MGPs, as accurate modeling is difficult to achieve or the established models do not accurately describe the actual dynamic processes.…”

Section: Control Situationmentioning

confidence: 99%

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

et al. 2016

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“…Another barrier to the commissioning of advanced control is that plants are often reluctant to permit advanced control vendors to monitor their processes remotely, which could offset the shortage of skilled manpower. PID control, as applied to grinding circuits, is discussed in Edwards et al (2002), Flament et al (1997), Desbiens et al (1997a) and Pomerleau et al (2000).…”

Section: Control Technologies Used In Milling Circuitsmentioning

confidence: 99%

“…Multivariable control is discussed in Pomerleau et al (2000), Hulbert et al (1990) and Craig and Macleod (1996). Numerous applications have indicated that model-based expert system controllers are useful when performing optimized supervisory control of natively complicated mineral processes Samskog et al (1996).…”

Section: Control Technologies Used In Milling Circuitsmentioning

confidence: 99%

Economic performance assessment of two ROM ore milling circuit controllers

Wei¹,

Craig²

2009

Minerals Engineering

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a b s t r a c tEconomic performance assessment of control systems is receiving increasing attention in both academia and industry. A relevant framework is proposed in Bauer and Craig (Bauer, M., Craig, I.K., 2008. Economic assessment of advanced process control -a survey and framework. Journal of Process Control 18 (1), 2-18) based on a comprehensive survey of the methods for economic analysis of advanced process control systems. The framework provides a formal procedure for the economic assessment of control systems. A practically motivated simulation study is used to cast the economic performance assessment of a nonlinear model predictive controller and three single-loop PID controllers for a run-of-mine milling circuit into this framework. Performance functions of the milling circuit, which dynamically relate the circuit process variables to monetary values, are developed based on a survey study on milling circuits and an in-depth literature study.

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A survey of grinding circuit control methods: from decentralized PID controllers to multivariable predictive controllers

Cited by 96 publications

References 6 publications

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

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

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

Economic performance assessment of two ROM ore milling circuit controllers

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