Robust control of a SAG mill

Galán, Omar; Barton, G.W.; Romagnoli, José A.

doi:10.1016/s0032-5910(02)00021-9

Cited by 25 publications

(10 citation statements)

References 1 publication

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“…These control methods involve decentralized PID control and model predictive control (MPC) (Pomerleau, Hodouin, Desbiens, & Gagnon, 2000;Ramasamy, Narayanan, & Rao, 2005), multivariable control (Duarte et al, 1999), robust control (Galan, Barton, & Romagndi, 2002), supervisory control (Radhakrishnan, 1999) and neurocontrol (Conradle & Aldrich, 2001). Although numerous advanced control strategies have been reported in control literatures, both at simulation, as well as experimental levels, very few of these currently operate in industry due to the complex process dynamics and severe disturbances in grinding circuits.…”

Section: Introductionmentioning

confidence: 99%

Expert system based adaptive dynamic matrix control for ball mill grinding circuit

Chen

Zhai

et al. 2009

Expert Systems with Applications

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Section: Introductionmentioning

confidence: 99%

Expert system based adaptive dynamic matrix control for ball mill grinding circuit

Chen

Zhai

et al. 2009

Expert Systems with Applications

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“…A SAG mill represents one of dominating units in a grinding circuit (Galan et al, 2002). A typical circuit consists of a SAG mill, a ball mill, a crusher, and mill discharge screens, together with primary and secondary cyclones.…”

Section: System and Data Descriptionmentioning

confidence: 99%

“…Control of a SAG mill, however, presents great challenges in terms of achieving stable and efficient operation. This is due to highly complex interactions of the process variables, as well as inadequacy of on-line process measurements (Apelt et al, 2001;Galan et al, 2002;Kapakyulu and Moys, 2007). Consequently, the advantage of SAG mills over conventional mills has not been fully realised.…”

Section: Introductionmentioning

confidence: 99%

SAG mill system diagnosis using multivariate process variable analysis

Ko¹,

Shang²

2011

Can J Chem Eng

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Semi-autogenous grinding (SAG) of ore plays a critical role in a mineral processing plant. In SAG operations, abnormal conditions, such as overload or insufficient ore holdup, often result in inefficient production and unstable operation. It is, therefore, essential to monitor the process using effective technology so that abnormal or faulty conditions can be detected and addressed in a timely manner. In this study, investigation is focused on applying multivariate analysis in the monitoring and diagnosing of an industrial SAG operation. The results show that principal component analysis provides an effective methodology for on-line monitoring and diagnosis. The detection and removal of faulty conditions will help to provide stable and cost-efficient operation.Le broyage semi-autogène (BSA) du minerai joue un rôle essentiel dans une usine de traitement des minéraux. Dans les activités de BSA, des conditions anormales, comme une surcharge ou une retenue du minerai insuffisante, mènent souventà une production inefficace et un fonctionnement instable. Il est, par conséquent, essentiel de surveiller le processusà l'aide d'une technologie efficace pour que les conditions anormales soient détectées et abordées de manière opportune. Dans ce document, l'enquête est axée sur l'utilisation d'une analyse multivariée dans le suivi et le diagnostic d'une activité de BSA industrielle. Les résultats indiquent que l'analyse des principaux composants fournit une méthodologie efficace pour le suivi et le diagnostic en ligne. La détection et le retrait de ses conditions anormales aiderontà procurer un fonctionnement stable et economique.

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“…Bourassa et al (1995) consider stability improvement and throughput increase to be important, but not energy savings. The reduction of energy consumption is nevertheless declared to be a primary benefit of process control in van Dyk et al (2000) and Galán et al (2002) because of the fast increasing mineral processing costs in recent years; throughput improvement is also considered important in these two works. Lo et al (1996) state that benefits resulting from process control mainly include throughput increase and power consumption reduction, and stability improvements are not regarded as crucial.…”

Section: The Economic Concerns Of Milling Circuit Control Systemsmentioning

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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Robust control of a SAG mill

Cited by 25 publications

References 1 publication

Expert system based adaptive dynamic matrix control for ball mill grinding circuit

Expert system based adaptive dynamic matrix control for ball mill grinding circuit

SAG mill system diagnosis using multivariate process variable analysis

Economic performance assessment of two ROM ore milling circuit controllers

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