Multivariable controller design for a hot rolling mill Abstract This paper describes a controller design for a hot rolling mill. The main purpose of the algorithm is to improve the control of the cross-width thickness profile of the plates. This is obtained by designing a controller which makes independent thickness control possible at the two ...
This paper describes a controller design for a hot rolling mill. The main purpose of the algorithm is to improve the control of the cross-width thickness profile of the plates. This is obtained by designing a controller which makes independent thickness control possible at the two sides of the rolling mill. This is obtained by first linearizing the positioning systems using feedback ...
This paper concerns the controller design for the hot rolling mill at the Danish Steel Works Ltd. The design is done using derived dynamical multivariable models. The main objective of the design is to separate the two sides of the rolling mill. This is obtained by first linearizing the positioning system using feedback linearization and then using eigenspace design on the linearized ...
this controller. SAG mills are the primary units in a grinding chain and also the most power consuming units. Therefore, improved control of SAG mills has the potential to signi cantly improve e ciency and reduce the speci c energy consumption for mineral processes. Grinding circuits involving SAG mills are multivariate processes.
Jan 01, 2009 ADVANCED CONTROL STRATEGY The Advanced Control Strategy Profit BALL was implemented using RMPCT Profit Controller from Honeywell, which has already been used successfully in SAG mill control. The operational objective for this strategy is To stabilize the circuit operation, with product particle size below a specified limit and aimed to ...
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
SAG mill 1 load control Plant staff, after extended testing and rigourous data analysis, determined that BrainWave reduced load variability by 14 while increasing production by 1.5. This was a great success for everyone involved. Assuming a copper price of 4 USDlb, ANDRITZ AUTOMATION estimates that BrainWave SAG mill led to an extra 12M USD
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.
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 power ...
Control of -SemiAutogenous GrindingSAG 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., amp Mainza, A.N. 2009.
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
The power draw, volumetric filling level, and a size reduction percentage were the controlled variables, while the fresh ore feed rate, fresh water feed rate, and the SAG rotation speed were the manipulated variables. The controller response showed a suitable control behavior independent of the noisy multivariable modification.
Jan 01, 2009 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
Keywords SAG mill, multivariable predictive control MPC, process control, advanced process control, nonlinear process, dynamic model. ... approach to face SAG mill controller specification. As ...
Jan 01, 2009 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.
Oct 01, 2014 2.4. Multivariable predictive control. In the present work, a three-input-three-output scheme of control was performed. The total water feed to the mill the feed water flow rate was added to the dilution water flow rate, so they could be specified separately, but for the SAG mill model, the total water content was the variable of interest, the fresh ore feed rate, and the mill rotation speed ...
The advanced process control team, formed by people from Informatics, Automation and Operations of CMDIC have assumed the challenge of generating the transition from a manual SAG Mill 1011 ...
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.
Integrated advanced process control with a sag mill monitor instrument to optimize mill performance . ... APC systems designed using techniques specifically suited for control of multivariable processes are aimed specifically at stabilization and optimization of process control. The results delivered by
Measurement of SAG Mill Parameters. Inferential measurements of SAG mill discharge and feed streams and mill rock and ball charge levels, detailed earlier in the series, are utilised in a simulation environment. A multi-variable, model predictive MPC controller simulation is
Dec 01, 2011 SAG mill system diagnosis using multivariate process variable analysis SAG mill system diagnosis using multivariate process variable analysis Ko, YoungDon Shang, Helen 2011-12-01 000000 Semiautogenous 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 ...
recent years, model predictive control MPC scheme, a widely used multivariable control algorithm in chemical process, has been applied in GC successfully 5-8 . Up to present, multivariable internal model control scheme has been a new and extensive concerned multivariable control algorithm in chemical process industries and other areas 9-13 .
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 ...
Figures 8 and 9 on the right show results from a gold plants SAG mill achieved with MillStars 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.