scholarly journals Model predictive control application in the energy saving technology of basic oxygen furnace

2019 ◽  
pp. 124-126
Author(s):  
Yurii Mariiash ◽  
Oleksandr Stepanets
Keyword(s):  
Model Predictive Control ◽  
Energy Saving ◽  
Predictive Control ◽  
Basic Oxygen Furnace ◽  
Main Task ◽  
Steel Smelting ◽  
Resource Saving ◽  
Equipment Operation ◽  
Energy Saving Technology ◽  
Control Application

In today's conditions of development, maximization of profitability and ensuring technological safety of metallurgical production, the tasks of developing resource-saving technological modes of steel smelting are urgent. The fulfilment of the condition for the simultaneous achievement of the desired chemical composition and temperature of the metal is ensured by controlling the oxygen consumption and the position of the oxygen impeller lance, therefore solving the problem of managing the blasting of the converter bath is the main task. The mathematical modelling of the bath purge during steel smelting for energy-saving technology is executed. The method for solving Model Predictive Control with quadratic functionality in the presence of constraints is given. The algorithms of work aimed at reliability of equipment operation and energy saving are introduced. Implementation of the described solutions will contribute to improving efficiency and reliability of equipment, increasing the proportion of scrap and reducing the melting period without changing of technological process.  

scholarly journals MODEL PREDICTIVE CONTROL APPLICATION IN THE ENERGY SAVING TECHNOLOGY OF BASIC OXYGEN FURNACE

2020 ◽  
Vol 10 (2) ◽  
pp. 70-74
Author(s):  
Oleksandr Stepanets ◽  
Yurii Mariiash
Keyword(s):  
Oxygen Consumption ◽  
Chemical Composition ◽  
Model Predictive Control ◽  
Energy Saving ◽  
Predictive Control ◽  
Basic Oxygen Furnace ◽  
Basic Oxygen ◽  
Melting Period ◽  
Energy Saving Technology ◽  
Control Application

The fulfilment of the condition for the simultaneous achievement of the desired chemical composition and temperature of the metal is ensured by controlling the oxygen consumption and the position of the oxygen impeller lance. The method for solving Model Predictive Control with quadratic functionality in the presence of constraints is given.  Implementation of the described solutions will contribute to increasing the proportion of scrap and reducing the melting period without changing of technological process.

A Novel Exergy-Based Optimization Approach in Model Predictive Control for Energy-Saving Assessment

2020 ◽  
Vol 31 (6) ◽  
pp. 1481-1488
Author(s):  
Karim Salahshoor ◽  
Mohammad. H. Asheri ◽  
Mohsen Hadian ◽  
Mehdi Doostinia ◽  
Masoud Babaei
Keyword(s):  
Model Predictive Control ◽  
Energy Saving ◽  
Predictive Control ◽  
Optimization Approach

Suboptimal Hybrid Model Predictive Control: Application to Sewer Networks

2008 ◽  
Vol 41 (2) ◽  
pp. 10021-10026 ◽  
Author(s):  
Carlos Ocampo-Martinez ◽  
Ari Ingimundarson ◽  
Alberto Bemporad ◽  
Vicenç Puig
Keyword(s):  
Model Predictive Control ◽  
Hybrid Model ◽  
Predictive Control ◽  
Control Application ◽  
Sewer Networks

scholarly journals A model predictive controller of the blowing mode during basic oxygen furnance process

2021 ◽  
pp. 61-66
Author(s):  
Oleksandr Stepanets ◽  
Yurii Mariiash
Keyword(s):  
Mathematical Model ◽  
Cast Iron ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Basic Oxygen Furnace ◽  
Scrap Metal ◽  
Basic Oxygen ◽  
The World ◽  
The Cost

Today in Ukraine and the world, the problem of energy saving and reducing the cost of smelted steel is state of art. Metallurgical enterprises are developing in conditions of fierce competition, the main reason is that Ukrainian products are extremely energy-intensive due to the depreciation of fixed assets and outdated technological processes. The basic oxygen furnace process is a process of producing steel from liquid cast iron with the addition of steel scrap to the converter and blowing oxygen from above through a water-cooling lance. Nowadays, the production of steel by BOF process is the most popular in the world and is becoming increasingly common. The main disadvantage of the basic oxygen furnace is the need to provide the initial amount of heat (in the form of liquid cast iron) and as a consequence - restrictions on the processing of scrap metal. Reducing the cost of basic oxygen furnace steel is achieved by increasing the share of scrap metal by increasing the degree of afterburning of CO to CO2 in the cavity of the converter, by optimal control of the parameters of the blast mode using model-predictive control. The principle of model-predictive control is based on a mathematical model of the plant. This approach minimizes the functional that characterizes the quality of the process. The linear-quadratic functional was chosen. A forecasting model is proposed taking into account the constraint on changing the position of the lance and the pneumatic oxygen supply valve. It was found that the change in the rate of decarburization of the metal depends on the distance of the lance to the level of the quiet bath and affects the degree of afterburning of CO to CO2. The decarburization process is non-stationary, described by a first-order inertial model, the transfer coefficient and time constant of which depends on the melting period and the duration of the purge. The mathematical model of the blast mode of oxygen-converter melting has been improved, taking into account the influence of the blast intensity on the decarburization process of the bath, which allowed to increase the accuracy and quality of blast control in terms of changing oxygen flow during purging. The simulation results of the automatic control system show that the model-predictive regulator provides the required level of carbon dioxide in the converter gases when the flow rate of oxygen for purge changes.

scholarly journals A MULTILEVEL RESOURCE-SAVING BLAST FURNACE PROCESS CONTROL

2021 ◽  
Vol 21 (1) ◽  
pp. 136-146
Author(s):  
T.A. Barbasova ◽  
Keyword(s):  
Blast Furnace ◽  
Model Predictive Control ◽  
Control Systems ◽  
Transient Process ◽  
Predictive Control ◽  
Blast Furnace Process ◽  
Resource Saving ◽  
Furnace Process ◽  
Operating Modes ◽  
Kohonen Neural Networks

A multilevel resource-saving blast furnace process control is considered. The resource-saving control is provided for operating, adaptation, technical and economic control in the automated systems of blast-furnace processes. It is proposed to form optimal operation modes of blast furnace heating, metal charge structures, natural gas and oxygen consumption. Decisions are made using Kohonen neural networks taking into account current and planned parameters of coke quality, iron ore, raw materials and blast. At the level of operating control, the work suggests a model predictive control to improve the resource conservation indicators. The method is based on decomposition of the general problem of the process dynamics identification on particular problems: dynamic synchronization and identification of process transfer functions. At the level of adaptive control, optimal operating modes of blast furnaces are expedient to be developed with respect to blast furnace heating, structure of metal charge, natural gas and oxygen rate considering the current and planned parameters of coke, blasting. The blast furnace operating modes are suggested to be determined based on Kohonen neural networks. In evaluating the efficiency of introducing the model predictive control, the existing actual statistics of scatter of BF mode parameters should be based upon. The fact is that the introduction of model predictive control assumes no radical change of the BF melt technology. Like in all the control systems, the BF process is considered as the set control object with all its characteristics. Changing process settings, raw material content does not introduce any cardinal variation in the scatter of process characteristics. However, in this case a transient process occurs which is necessary for the control system to identify the changing conditions. The transient process is inherent to all the control systems and the blast furnace process is not an exclusion. As a result of transient process, the control system is set to the optimal mode.

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