Non-linear model predictive control of throughput and strip temperature for continuous annealing line

Wu, Hao; Speets, Ramon; Heeremans, F.; Driss, O. Ben; Buren, R. van

doi:10.1179/1743281214y.0000000263

Cited by 23 publications

(24 citation statements)

References 16 publications

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“…The furnaces include many heating zones with large number of R/Ts and long strip path with many deflection rolls. When the nonlinear MPC is used, it solves optimization problems for nonlinear models with long horizon as time response of the inputs is slow; thus, the optimization consumes a significant amount of time and especially highly dependent on the number of states [21], [34].…”

Section: A Problem Statementmentioning

confidence: 99%

“…MPC is widely used in many practical systems [32]- [35]. MPC has been used to control the temperature of the strip in consideration of strip changes with long prediction horizons because the time response of the input is slow [2], [5], [9], [12], [21]. The MPC performance is highly dependent on the accuracy of the predictive model.…”

Section: Introductionmentioning

confidence: 99%

“…However, if there are unknown parameters, prediction using the model is not possible. For real time MPC, the unknown parameter should be estimated online as the unknown parameters vary during the operation [21], [32]- [34], [34].…”

Section: Introductionmentioning

confidence: 99%

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Low-Order Model Identification and Adaptive Observer-Based Predictive Control for Strip Temperature of Heating Section in Annealing Furnace

et al. 2021

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The heating section of an annealing furnace is a plant that raises the temperature of steel strips to the desired target temperature to ensure that the strips achieve the desired material properties. Model predictive control (MPC) has been used to increase the temperature in previously published studies, because it reflects the geometrical and material characteristics of the strip. An accurate temperature predictive model for the annealing furnace is required for the optimization of the MPC. For a large and complex annealing furnace, nonlinear models from existing studies are computationally expensive. Therefore, we propose identification method of a linear low-order model, and then apply it to the MPC. In addition, we introduce parameter estimation and an adaptive observer for the estimation to address difficulties in identifying unknown parameters. To verify the identified model and adaptive observer-based MPC, control results from the tracking of target temperature are shown and analyzed through a simulation with conditions close to the actual operation conditions. Furthermore, the simulation results of the proposed method are compared with those of the PI controller and nonlinear MPC. The proposed method solves the problems caused by the massive computational complexity and absence of sensors. The proposed method allows for the accurate control of the temperature using MPC in various types of annealing furnaces.

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Section: A Problem Statementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Low-Order Model Identification and Adaptive Observer-Based Predictive Control for Strip Temperature of Heating Section in Annealing Furnace

et al. 2021

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“…There are several references in the literature about furnace models: some of them require the use of FEM, which entails an increase in complexity and longer computational time in case of 3D [6], but can be simplified to 2D and used online [7]; others, based on neural networks [8,9], are used to monitor the performance of the furnace over time; and finally, there are some models including combustion [10,11] that fulfill control purposes with a certain degree of accuracy. There are some other examples of modelling of the complete furnace system, including the furnace rolls and the combustion process [6,[12][13][14][15], however, none of these different approaches use the radiant tube temperatures or the status of the radiant tubes as is proposed in the model presented in this paper.…”

Section: Introductionmentioning

confidence: 99%

Practical thermal model for a radiant tubes annealing furnace

Garcia-Martino

Prieto

2020

Metall. Res. Technol.

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Modeling of vertical radiant tube annealing furnaces has proven to be one of the best tools to improve the performance of a galvanizing line. However, there is a lack of a practical model able to consider the temperature and status of the radiant tubes, which are key elements in the capacity of the furnace. The model proposed divides the furnace in several segments and compares the radiated heat, that is exchanged between the radiant tubes and the strip, and the heat required to increase the temperature of the mass flow on the strip. This comparison is represented as an implicit equation where the strip's temperature is obtained by iteration. The model is validated calculating the final temperature of more than five hundred coils divided in four different steel families. The 90% of the calculated temperatures are within a 2% deviation range compared to the measured temperatures. This model combines good accuracy in the results with low computational times, allowing the simulation of hundreds of coils in a few minutes.

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“…Deviation defect refers to the asymmetric tension on both sides of the strip and the different aligning force. Thus, the strip deviates from the centre of the production line and moves to one side of the roller [1][2][3][4][5]. The so-called buckling defect refers to the exposure of the strip to uneven stress, as well as to the transverse compressive stress.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive optimisation technology of roller profile in continuous annealing furnace

Wang

Bai

Zhang

et al. 2017

Ironmaking & Steelmaking

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Several problems, such as strip deviation and buckling, are encountered in the continuous annealing process. In this study, equipment and process features of continuous annealing, as well as the advantages and disadvantages of single taper roller and double taper roller in the prevention and treatment of the buckling and strip deviation were considered. Basing on a number of field experiments and theoretical studies, a new set of furnace roller profile curve was proposed and a set of optimisation model suitable for furnace roller was established, with travelling stability of the strip as the objective function. Test results of field production showed that the strip exhibited high speed and stability after optimisation, and the service cycle of the furnace roller was considerably improved. The results of this study provide an important economic benefit for the site and are valuable for further popularisation and application.

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Non-linear model predictive control of throughput and strip temperature for continuous annealing line

Cited by 23 publications

References 16 publications

Low-Order Model Identification and Adaptive Observer-Based Predictive Control for Strip Temperature of Heating Section in Annealing Furnace

Low-Order Model Identification and Adaptive Observer-Based Predictive Control for Strip Temperature of Heating Section in Annealing Furnace

Practical thermal model for a radiant tubes annealing furnace

Comprehensive optimisation technology of roller profile in continuous annealing furnace

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