Soft Constrained based MPC for Robust Control of a Cement Grinding Circuit

Prasath, Guru; Recke, Bodil; Chidambaram, M.; Jørgensen, John Bagterp

doi:10.3182/20131218-3-in-2045.00183

Cited by 8 publications

(14 citation statements)

References 2 publications

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“…The investigation in [1] exploited the correlation between elevator load and fineness to design a controller for cement grinding mill. The elevator load was varied by changing the feed-flow rate and separator speed.…”

Section: Control Strategymentioning

confidence: 99%

“…Usually, the cement grinding circuit model is nonlinear [1]. To design predictive controllers, the non-linear model is linearized around an operating point and then a controller is designed around that working region.…”

Section: Process Modellingmentioning

confidence: 99%

“…The transfer function thus obtained from the system identification toolbox is given in equation (1).…”

Section: Process Modellingmentioning

confidence: 99%

“…Feed-grindability variations occur due to lack of homogeneity in clinkers procured from different vendors. Current practice in cement industries is to maintain the separator power constant and vary the separator speed for maintaining fineness [1]. This conventional way of controlling the fineness becomes ineffective beyond a particular operating range of separator when there are feed-grindability variations.…”

Section: Introductionmentioning

confidence: 99%

“…In spite of such advantages, their performance is limited by the model accuracy and uncertainties in the process. Motivated by this, Guruprasath et al [1] studied the use of model predictive controllers (MPCs) for cement grinding circuit. The proposed controller was not only optimal, but also handled model complexities, and constraints, inherently in its design.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Generalized Predictive Controller for Ball Mill Grinding Circuit in the Presence of Feed-grindability Variations

Venkatesh¹,

Ramkumar²,

Muralidharan³

et al. 2016

SIC

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Feed-grindability variations (clinker hardness) in cement grinding circuit affects the product quality and productivity of the cement plant. This investigation proposes a generalized predictive controller for cement grinding circuit that is more robust to feed-grindability variations. The main building block of the proposed controller is a new model for cement grinding circuit that directly relates product quality with elevator current and main drive load. The advantage of the model is that the effect of feed-grindability variations on product quality can be easily observed from the output. To develop such a model, this investigation adapts a data driven modelling approach. Experimental data obtained as measurements from cement grinding circuit in a cement mill located near Chennai, India is used to develop the transfer function model based on least squares approach. The model obtained from data driven modelling is used to design a generalized predictive controller whose objective is to optimize the product quality in the presence of feed-grindability variations without breaching physical and operational limits of the cement grinding circuit. The tuning parameters of the proposed generalized predictive controller is adjusted to meet performance metrics specific to cement industries. Our results show that the proposed controller provides better product quality in the presence of feed-grindability variations than other optimization based controllers such as the linear quadratic regulator.

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Section: Control Strategymentioning

confidence: 99%

Section: Process Modellingmentioning

confidence: 99%

“…The transfer function thus obtained from the system identification toolbox is given in equation (1).…”

Section: Process Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%