adequately control the mill; resulting in poor stability, frequent operator interventions and less than optimum performance. This paper describes the successful integration of advanced field systems such as mill feed image analysis (Wipfrag) and crusher gap controller (ASRi), into a multi-variable fuzzy logic SAG mill controller.

Grinding MPC was implemented in the SAG Mill in June 2015. This pilot application, called Phase 1, featured one of the first Multivariable Predictive Controllers to be installed in a Canadian mineral processing plant. Since the implementation of MPC, gold recovery from the gravity circuit has increased.

Mill Process Control Automation Control System Back. Ore Receiving; Solids Level Measurement ... Multivariable Transmitters Low Power Environmental Solutions Remote Automation & SCADA ... (SAG) Mill Back. Cyclone Control; Expert Cyclone Control Cyclone Control Back. Acid Plant ...

Manta Controls ® have developed the Manta Cube ® system where it is available for SAG Mill Control, AG Mill Control, Ball Mill Control, Flotation Control, Thickener Control and CCD Control. Control of other process units are also available. ... ranging from regulatory control through to advanced multivariable control systems depending on the ...

The controller response showed a suitable control behavior independent of the noisy multivariable modification. Highlights • MIMO control system design based on the MPC strategy for a SAG mill. • Control action exhibit an additional effort in the water as manipulated variable.

In the last decades approaches varying from decentralized PID control to multivariable predictive control have been applied to control of SAG mills with variable success; at …

A study of control strategy for the bin system with tube mill in the coal fired power station. ISA TRANSACTIONS. 2002, 41 (2): 215-224 (SCI) Zhang TJ, Lu JH. A pso-based multivariable Fuzzy Decision-Making predictive controller for a once-through 300MW power plant CYBERNETICS AND SYSTEMS. 2006, 37 (5): 417-441 (SCI) ...

Control of -SemiAutogenous Grinding(SAG) mill weight is an example of an important process that exhibits many of these aspects. Maintaining the SAG mill weight at the optimum value is critical for achieving maximum grind rate efficiency and mill production (Powell, M.S., van der Westhuizen, A.P., & Mainza, A.N. 2009).

Figures 8 and 9 on the right show results from a gold plant's SAG mill achieved with MillStar's Segregated Ore Feed Controller combined with the Power Optimiser: • The standard deviation of the mill feed control is greatly reduced. • The cyclone feed is more stable, allowing for consistent size separation and feed to downstream processes.

The application of a multivariable regulator to a hot strip finishing mill is considered. The need for multivariable control is due to the interactions between the strip thickness, tension and the angle of the looper arm. A much improved performance was obtained by designing a controller which takes account of the interactions effectively which a …

In this study, a fuzzy logic self-tuning PID controller based on an improved disturbance observer is designed for control of the ball mill grinding circuit. The ball mill grinding circuit has vast applications in the mining, metallurgy, chemistry, pharmacy, and research laboratories; however, this system has some challenges. The grinding circuit is a …

However, adjusting the mill speed to the optimal state presents a very challenging problem. In a SAG mill, the speed control system is a nonlinear and strongly coupled multivariable system. The proportional integral (PI) vector control method is used in the mill control system . The PI vector control method cannot meet the requirements of high ...

SAG Mill Control Strategy using Profit Controller "ProfitSAG" applications have been implemented using Honeywell technology called "Profit ControllerTM"; this is a Multivariable Predictive Control algorithm based on models, also known as RMPCT (Robust Multivariable Predictive Control Technology).

concentrator site in order to tightly control the weight in the SAG mill to promote optimum grinding. This stra-tegy has improved mill throughput by 5.9%, reduced feed variability by 5.6%, and reduced energy consumption per tonne by 5.4%. Once BrainWave was installed, the improvement was

The controller response showed a suitable control behavior independent of the noisy multivariable modification. AB - The present manuscript focuses on the development of a multivariable control based on the MPC strategy for a semiautogenous grinding (SAG) device.

A multivariable controller for a hot rolling mill which uses rolling stand speeds to control exit strip temperature and interstand tension, wherein the controller considers the inherent multivariable nature of the tension and temperature processes relative to individual rolling stand speeds by employing a cross-correlation transfer function matrix which is decoupled by …

Precise control of SAG mill loading and flotation cell level is critical to maximize production and recovery in mineral concentrators. While expert systems are commonly used to optimize these process operations, the underlying regulatory control is often implemented using traditional proportional-integral

Ciprano et al 1989, Rajamani et al 1991). The first successfully implemented multivariable process control (MPC) is described for a SAG mill circuit in a bauxite processing refinery at Wagerup, Australia (Refs: Gopinath, Mathur et al, 1995 and Le Page, Freeman et al 1996, Luse, Mathur et al 1997). The MPC

The behavior of the SAG mill circuit is multivariable i.e. exhibit complex interactions and nonlinear behavior between the process variables. It is also dynamic i.e. delay times between variables within the process need to be considered before control actions are executed. Given these challenges, the objectives for acceptable SAG mill operation ...

1. The SAG mill speed (rpm) 2. The SAG mill power (MW) 3. The SAG mill feed rate (tph) 4. The SAG mill weight (tonnes) Figure 10. The performance of Train 1 SAG Mill - before the new Manta Cube. It can be seen from this set of operational data that the mill weight varies over a wide range and this is consistent with normal operator control of a ...

multivariable predictive control in a way that provides immediate returns, we work with them to ensure benefits continue to be realized over the long ... SAG Mill Rod Mill Ball Mill Stirred Mill Flotation(train) Thickener/WasherTrain Induration Furnace Kiln-Roaster Acid Plant SXEW(train) Digestion(autoclave)

"The control of the operation of semi autogeneous grinding (SAG) mills is mainly achieved through adjustments of feed rate, water addition and speed of rotation. With the introduction of image based sensors it is possible to have on-line measurements of the size distribution of the ore feeding a SAG mill.

Taking into account the complexity and the dynamics of the close grinding circuits (most popular in the mineral processing industry) the most suitable solution would be to measure or model the mill's output itself. The necessity of robustness and complexity of multivariate nonlinear predictive control of SAG ball mills is underlined in .

the only grinding control is to maximize the power drawn by the mill. Unfortunately, the relation between power and grinding performance is a complex and non-linear function. Development of advanced control systems has helped the situation considerably. However, these systems still …

Stable control of the ball mill grinding process is very important to reduce energy losses, enhance operation efficiency, and recover valuable minerals. In this work, a controller for the ball mill grinding process is designed using a combination of model predictive control (MPC) with the equivalent-input-disturbance (EID) approach.

A.1. H l -controller design for SAG millThe first step in the design of a robust controller for the SAG mill involves obtaining linear dynamic models (expressed as transfer functions) for the impact of the manipulated variable (i.e. feed flowrate) and the disturbance (i.e. the F 80 parameter) on the variable to be controlled (i.e. the SAG mill ...

Keywords: SAG mill, multivariable predictive control (MPC), process control, advanced process control, nonlinear process, dynamic model. ... approach to face SAG mill controller specification. As ...

Since 2007, a number of Multivariable Predictive Control (MPC) Applications have been implemented on SAG mills, among others, within the Kairos Mining Concentrator Automation Program using "Profit...

Hadizadeh et al. described application of a fuzzy control system to the SAG mill grinding circuits. Proposed advanced control system tested in a copper grinding circuit [19] .

SmartGrind TM controller is a marriage of multivariable predictive control (MPC) with techniques that provide ... Controlling a SAG mill is a non-linear problem near capacity constraints. Designing a controller that addresses the above issues can be split into 2 groups.

The Multivariable Predictive Controller proposed in this paper can set the SAG Mill operation in the optimal zone maximizing profits without restriction violation. The supervisory strategy finds the optimal Hold Up set-point by performing simple online calculations.

T1 - Model predictive control of semiautogenous mills (sag) AU - Salazar, José Luis. AU - Valdés-González, Héctor. AU - Vyhmesiter, Eduardo. AU - Cubillos, Francisco. PY - 2014/10/1. Y1 - 2014/10/1. N2 - The present manuscript focuses on the development of a multivariable control based on the MPC strategy for a semiautogenous grinding (SAG ...

Model Predictive Control. The behavior of the SAG mill circuit is multivariable ie exhibit complex interactions and nonlinear behavior between the process variabl It is also dynamic ie delay times between variables within the process need to be considered before control actions are executed Given these challenges the objectives for acceptable SAG mill operation...

With mill overloading a major cause of plant downtime, the company used its Control Performance Optimizer to create a simulator that would give the mill staff a better understanding of their grinding circuit, as well as developing a mill charge-volume estimator to provide real-time feedback on the state of the mill. The company described ...

The Multivariable Predictive Controller proposed in this paper can set the SAG Mill operation in the optimal zone maximizing profits without restriction violation. The supervisory strategy finds the optimal Hold Up set-point by performing simple online calculations.

SAG Mill Circuit Example — Gold Processing SAG mill circuit example for gold processing [image: (135-6-3)] AG/SAG Mill. AG/SAG mills are normally used to grind run-off-mine ore or primary crusher product. Wet grinding in an AG/SAG mill is accomplished in a slurry of 50 to 80 percent solids. 2D and 3D simulations of particles in a SAG Mill. More

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