Temperature control of reheating furnace based on distributed model predictive control

Nguyen, Xuan Manh; Rodríguez-Ayerbe, Pedro; Lawayeb, Fayçal; Dumur, Didier; Mouchette, Alain

doi:10.1109/icstcc.2014.6982504

Cited by 6 publications

(7 citation statements)

References 3 publications

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“…In this context, traditional control systems, Advanced Process Control (APC) systems, and high-level optimization systems can be utilized [3,12]. These systems in the steel industry reheating furnaces can be located at levels 1, 2, and 3 of the automation hierarchy [13]. Different researchers, engineers, and practitioners proposed various types of solutions located at the mentioned levels of the automation hierarchy.…”

Section: Introductionmentioning

confidence: 99%

“…The computation takes into account the required zone temperature setpoint (provided by level 2) in order to track it. Examples of level 1 control solutions were reported in [13][14][15][16][17][18][19]. A distributed Model Predictive Control (MPC) strategy is proposed in [13], using a model which considers the coupling effect between zones.…”

Section: Introductionmentioning

confidence: 99%

“…Examples of level 1 control solutions were reported in [13][14][15][16][17][18][19]. A distributed Model Predictive Control (MPC) strategy is proposed in [13], using a model which considers the coupling effect between zones. A comparison between the proposed control strategy and a standard Proportional-Integral-Derivative (PID)-based controller is provided through tailored experiments.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Mode Model Predictive Control Approach for Steel Billets Reheating Furnaces

Zanoli

Pepe

Orlietti³

2023

Sensors

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In this paper, a unified level 2 Advanced Process Control system for steel billets reheating furnaces is proposed. The system is capable of managing all process conditions that can occur in different types of furnaces, e.g., walking beam and pusher type. A multi-mode Model Predictive Control approach is proposed together with a virtual sensor and a control mode selector. The virtual sensor provides billet tracking, together with updated process and billet information; the control mode selector module defines online the best control mode to be applied. The control mode selector uses a tailored activation matrix and, in each control mode, a different subset of controlled variables and specifications are considered. All furnace conditions (production, planned/unplanned shutdowns/downtimes, and restarts) are managed and optimized. The reliability of the proposed approach is proven by the different installations in various European steel industries. Significant energy efficiency and process control results were obtained after the commissioning of the designed system on the real plants, replacing operators’ manual conduction and/or previous level 2 systems control.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-Mode Model Predictive Control Approach for Steel Billets Reheating Furnaces

Zanoli

Pepe

Orlietti³

2023

Sensors

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“…In a WBF, the slabs are walked in a cyclic movement, through heating zones of different temperatures. From an energy efficiency perspective, this process plant is one of the most energy consuming systems in the steel industry [1]. Therefore, an efficient controller is needed to minimize the energy cost for the generated heat.…”

Section: Introductionmentioning

confidence: 99%

“…However, the performance of these controllers are not always satisfactory, due to the existence of large time varying delays and the high interaction between the control loops [11]. Alternative popular control schemes, relies on the framework of the Model Predictive based Control (MPC) as in [12] and [13]. These approaches, in spite of a good MPC's performance in controlling the temperature and handling the constraints, may not be practical in case of model mismatches and high plant disturbances, while for a satisfactory operation, a high number of utilized tunning parameters is needed.…”

Section: Introductionmentioning

confidence: 99%

On control structure design for a walking beam furnace

Jafari

Arranz

Gustafsson

et al. 2017

2017 25th Mediterranean Conference on Control and Automation (MED)

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Abstract-The aim of this article is to introduce a novel sparse controller design for the temperature control of an experimental walking beam furnace in steel industry. Adequate tracking of temperature references is essential for the quality of the heated slabs. However, the design of the temperature control is hindered by the multivariable (non-square) dynamic behavior of the furnace. These dynamics include significant loop interactions and time delays. Furthermore, a novel datadriven model, based on real life experimental data that relies on a subspace state representation in a closed loop approach is introduced. In the sequel, the derived model is utilized to investigate the controller's structure. By applying the relative gain array approach a decentralized feedback controller is designed. However, in spite of the optimal and sparse design of the controller, there exists interaction between loops. By analyzing the interaction between the inputs-outputs with the Σ2 Gramian-based interaction methodology, a decoupled multivariable controller is implied. The simulation result, based on the experimental modeling of the furnace, shows that the controller can successfully decrease the interaction between the loops and track the reference temperature set-points.

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The modeling and identification of walking beam type slab reheating furnace based on immersion and invariance disturbance estimation

Kavak,

Yalçın

2023

Control Engineering Practice

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Temperature control of reheating furnace based on distributed model predictive control

Cited by 6 publications

References 3 publications

Multi-Mode Model Predictive Control Approach for Steel Billets Reheating Furnaces

Multi-Mode Model Predictive Control Approach for Steel Billets Reheating Furnaces

On control structure design for a walking beam furnace

The modeling and identification of walking beam type slab reheating furnace based on immersion and invariance disturbance estimation

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