Billet Heating Time Forecast when Implementing Optimal Control of Heating Process with Regard to Mill Performance

Андреев, С. М.; Panov, Aleksandr I.; Parsunkin, B. N.

doi:10.1109/rusautocon.2019.8867671

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…First, the delay operations is studied by some researchers on the supervisory scheduling controller by solving the scheduling optimization problems. For instance, Andreev et al 15 describes a method of routine slab heating time correction in the delay event of rolling mill's process equipment accidents. Shikimori et al 16 develop an automatic rolling scheduling system for the synchronized operation when a delayed direct‐slab is included in a rolling schedule.…”

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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Section: Introductionmentioning

confidence: 99%