Simultaneous optimization of slab permutation scheduling and heat controlling for a reheating furnace

Suzuki, Masayasu; Katsuki, Kenji; Imura, Jun-ichi; Nakagawa, Junichi; Kurokawa, Tetsuaki; Aihara, Kazuyuki

doi:10.1016/j.jprocont.2013.10.007

Cited by 19 publications

(7 citation statements)

References 10 publications

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“…In some other works, the temperature distribution inside a billet is calculated by a 2-dimensional model. [11][12][13][14][15][16][17] Basing on this type of model, finite volume method is generally used to solve the radiative heat transfer equation. 11,12) Optimization for the heating schedule and energy conversation are extended and applied.…”

Section: Analysis Of Billet Thermal Behavior and Temperature Setting mentioning

confidence: 99%

“…11,12) Optimization for the heating schedule and energy conversation are extended and applied. [13][14][15] And comparison research of different thermal models and simplification methods are introduced in some papers. [16][17][18] Meanwhile, a full 3-dimensional temperature field is studied in recent research work.…”

Section: Analysis Of Billet Thermal Behavior and Temperature Setting mentioning

confidence: 99%

“…It should be calculated according to the current thermal state. Step5: With the obtained values, the hot gas blackness ε g can be calculated by (13). Accordingly φ g can be obtained by (12).…”

Section: )mentioning

confidence: 99%

See 2 more Smart Citations

Analysis of Billet Thermal Behavior and Temperature Setting Optimization in a Walking Beam Reheat Furnace

Tang²

2017

ISIJ Int.

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Section: Analysis Of Billet Thermal Behavior and Temperature Setting mentioning

confidence: 99%

Section: Analysis Of Billet Thermal Behavior and Temperature Setting mentioning

confidence: 99%

See 1 more Smart Citation

Analysis of Billet Thermal Behavior and Temperature Setting Optimization in a Walking Beam Reheat Furnace

Tang²

2017

ISIJ Int.

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“…In [20], the model-based temperature predictive control problem is devised by segmenting the advection equation temporally and spatially employing the method of characteristics and regionally employing linear approximations for the nonlinear constituent. These model-based temperature control methods realize temperature predictive control, feedforward control and feedback control [21][22][23][24]. However, for some industrial processes, it is very difficult to develop a precise temperature control model.…”

Section: Introductionmentioning

confidence: 99%

Multi-Zone Integrated Iterative-Decoupling Control of Temperature Field of Large-Scale Vertical Quenching Furnaces Based on ESRNN

Shen

Chen

2023

Processes

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Temperature uniformity within a large vertical quenching furnace is the key factor to determine the properties of aluminum workpieces. The existing temperature control method for quenching furnaces cannot overcome the influence of multi-zone coupling issues, which lead to unstable product performance and a lack of key performance. Based on a workpiece temperature field model, a spatial-temporal dimensional extrapolation method is proposed to realize fast and accurate solving of the temperature model. In view of the over-burning and under-burning problems during the temperature rising period, a self-incentive nonparametric adaptive iterative control algorithm is presented, which realizes consistent temperature rising of multiple heating zones. Aiming at the strong coupling problem of the multi-zone heating manner during the temperature holding period, the decoupling problem of multiple control loops is converted into a multi-loop integrated control optimization problem. An eigenvector self-update recurrent neural network (ESRNN) is constructed to determine the Jacobian information and tune the control parameters of each loop controller in real time, thereby realizing the integrated intelligent decoupling control of multiple heating loops. Simulation and industrial results verify the superiority of the proposed method, which can realize high-precision and high-uniformity control of a large-scale temperature field and effectively improve the quality and performance of aluminum alloy workpieces.

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“…The MPC controller uses a numerical nonlinear model to solve a constrained dynamic optimization problem by the Nelder‐Mead simplex algorithm. Similarly, Masayasu Suzuki et al 9 propose a hybrid model predictive control method, which is composed of a nonlinear advection equation. Fujii et al 10 propose a novel modeling scheme for model predictive control of slab reheating furnace in a hot strip mill.…”

Section: Introductionmentioning

confidence: 99%

A combined adaptive entropy‐TOPSIS and model predictive control strategy for mixed loading and delay operations in the reheating furnace

Yang

Luo

Qiao

2023

Optim Control Appl Methods

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SummaryIn this paper, a combined adaptive entropy‐TOPSIS and model predictive control strategy is proposed to deal with the mixed loading and delay operations in the reheating furnace. Firstly, the mathematical models consistent with the behaviour of the real reheating furnace are built to describe the complicated heat exchange process. Secondly, a dynamical optimization problem for the mixed loading operation and delay operation in the walking beam reheating furnace is obtained. To adjust the weighting factors of the optimization problem in real time, the adaptive entropy‐TOPSIS method is proposed. Then, the rolling horizon approach is applied to solve the proposed optimization problem. Finally, numerical experiments and simulation analysis are undertaken to verify the reliability and accuracy of the proposed strategy. The simulation results demonstrate that the proposed strategy can deal with three typical cases of delays effectively and the control accuracy is successfully improved from 74.79% to 99.17%.

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Simultaneous optimization of slab permutation scheduling and heat controlling for a reheating furnace

Cited by 19 publications

References 10 publications

Analysis of Billet Thermal Behavior and Temperature Setting Optimization in a Walking Beam Reheat Furnace

Analysis of Billet Thermal Behavior and Temperature Setting Optimization in a Walking Beam Reheat Furnace

Multi-Zone Integrated Iterative-Decoupling Control of Temperature Field of Large-Scale Vertical Quenching Furnaces Based on ESRNN

A combined adaptive entropy‐TOPSIS and model predictive control strategy for mixed loading and delay operations in the reheating furnace

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