The consistency control of mold level in casting process

Shen, Ping; Li, Han-Xiong

doi:10.1016/j.conengprac.2017.02.011

Cited by 8 publications

(2 citation statements)

References 32 publications

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“…Periodic disturbances have always been observed in continuous casting, mainly for slab. Many control solutions have been proposed, but their complete understanding and compensation is still complex [26,28]. Unclogging and sudden changes of casting speed are sudden disturbances with a damaging effect that can be compensated for with a control approach of well sudden disturbance rejection [2,29].…”

Section: Process Descriptionmentioning

confidence: 99%

Neuro-Fuzzy System for Compensating Slow Disturbances in Adaptive Mold Level Control

González-Yero

Leyva

Mendoza

et al. 2020

Metals

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Good slow disturbances attenuation in a mold level control with stopper rod is very important for avoiding several product defects and keeping down casting interruptions. The aim of this work is to improve the accuracy of the diagnosis and compensation of an adaptive mold level control method for slow disturbances related to changes of stopper rod. The advantages offered by the architecture, called Adaptive-Network-based Fuzzy Inference System, were used for training a previous model. This allowed learning based on the process data from a steel cast case study, representing all intensity levels of valve erosion and clogging. The developed model has high accuracy in its functional relationship between two compact input variables and the compensation coefficient of the valve gain variations. The future implementation of this proposal will consider a combined training of the model, which would be very convenient for maintaining good accuracy in the Fuzzy Inference System using new data from the process.

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Section: Process Descriptionmentioning

confidence: 99%

Neuro-Fuzzy System for Compensating Slow Disturbances in Adaptive Mold Level Control

González-Yero

Leyva

Mendoza

et al. 2020

Metals

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“…However, these authors used an adaptive controller because the proportional-integral-derivative (PID) controller is not robust with respect to nonlinearities and clogging disturbances [13,14]. The study by Shen [15] proposed a multiple periodic disturbance rejection controller for the casting process by using the disturbance observer and a bulging frequency detection system that used a group of filters, the fast Fourier transform (FFT) algorithm, and the null crossing detection.…”

Section: Introductionmentioning

confidence: 99%

A Model-Based Predictive Controller of the Level of Steel in the Mold with Disturbances Using a Repetitive Structure

Pereira

Almeida

Salles

et al. 2021

Metals

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Keeping the level of steel in the mold of the continuous casting process constant is fundamental for the quality of the steel produced and, consequently, its commercial value. It is challenging, considering the several disturbances that cause undesired variations in the mold level. The aim of this paper is to apply a repetitive structure composed of two controllers, a generalized predictive controller (GPC) and a repetitive GPC (R-GPC) with constraints to mitigate the bulging and clogging/unclogging disturbances and the casting speed variation in the mold level of the process. The R-GPC controller has the same characteristics as the GPC, such as performance, robustness to disturbances, and insertion of constraints, and its advantage is the elimination of periodic disturbances. The repetitive structure will be implemented with a robustness filter and tuned by a genetic algorithm (GA). The controller tests are performed by simulations of a nonlinear mathematical model of the mold level, validated using real data from the steel industry. The proposed controller reduces the bulging disturbance amplitude by 98.5% and at 25% of the frequency of reversions in the valve. Consequently, the proposed controller allows an increase in the valve life span, a reduction in maintenance costs, and quality improvement in the steel slab.

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Novel consistency control strategy for jet dispensing

Shen

2018

J. Cent. South Univ.

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The consistency control of mold level in casting process

Cited by 8 publications

References 32 publications

Neuro-Fuzzy System for Compensating Slow Disturbances in Adaptive Mold Level Control

Neuro-Fuzzy System for Compensating Slow Disturbances in Adaptive Mold Level Control

A Model-Based Predictive Controller of the Level of Steel in the Mold with Disturbances Using a Repetitive Structure

Novel consistency control strategy for jet dispensing

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