Optimal control of the blowing mode parameters during basic oxygen furnace steelmaking process

2021 ◽  
pp. 94-96
Author(s):  
Yurii Mariiash ◽  
Oleksandr Stepanets
Keyword(s):  
Optimal Control ◽  
Model Predictive Control ◽  
Predictive Control ◽  
System Modeling ◽  
Basic Oxygen Furnace ◽  
Steel Scrap ◽  
Quadratic Functional ◽  
Steelmaking Process ◽  
Basic Oxygen ◽  
Control Approach

The oxygen converter is intended for production of steel from liquid cast iron and steel scrap at blowing by oxygen. Nowadays, Basic Oxygen Furnace process is the main method for steelmaking. The main disadvantage of the basic oxygen furnace is the limited ability to increase the part of scrap metal. The task of the proposed approach is to control of the blowing mode parameters to establish the optimal level of CO2 that will ensure a minimum specific cost of steel in the presence of restrictions and boundary conditions of basic oxygen furnace steelmaking process. A model predictive control taking into account the constraints on the input signals and the quadratic functional is proposed.  The design of Model Predictive Control is based on mathematical model of an object. This approach minimizes the cost function that characterizes the quality of the process. The result of the automatic control system modeling shows that the Model Predictive Control approach provides retention of carbon dioxide level when oxygen consumption is changing. The obtained quadratic functional is optimized to find the optimal control of blowing parameters.

scholarly journals MODEL PREDICTIVE CONTROL TOOLBOX DESIGN FOR NONSTATIONARY PROCESS

2021 ◽  
Author(s):  
Oleksandr V. Stepanets ◽  
Yurii I. Mariiash
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Complex Structure ◽  
Nonstationary Process ◽  
Actual State ◽  
Quadratic Functional ◽  
Linear Quadratic ◽  
Prediction Horizon

Background. Model predictive control (MPC) approach is the basic feedback scheme, combined with high adaptive properties, which determines its successful use in the practice of design and operation of control systems. These advantages allow managing multidimensional objects with a complex structure, including nonlinearity, optimizing processes in real time within the constraints on controlled and managed variables, taking into account uncertainties in the task of objects and perturbations. Objective. The purpose of the paper is to design and analyse control system of carbon monoxide oxidation in the convector cavity based on MPC with linear-quadratic cost functional with constraint. Methods. The design of MPC is based on mathematical model of an object (relatively simple). At the current step, the prediction of object dynamic response on some final period of time (prediction horizon) is carried out; control optimization is performed, the purpose of which is to approximate the control variables of the prediction model to the corresponding setpoint on the predict horizon. The found optimal control is applied and measurement of an actual state of object at the end of a step is carried out. The prediction horizon is shifted one step further, and this algorithm are repeated. Results. The results of modeling the automatic control system show that the MPC approach provides maintenance of carbon dioxide content when changing oxygen consumption and overshoot caused by introduction bulk does not exceed 0.6 % that meets the technological requirements of the process. Conclusions. A fuse of the MPC and the quadratic functional given the constraints on the input signals is proposed. The problems of control degree of carbon oxidation in the convector cavity include non-stationarity, so the use of classical control methods is difficult. The MPC approach minimizes the cost function that characterizes the quality of the process. The predicted behaviour of a dynamic system will usually differ from its actual motion. The obtained quadratic functional is optimized to find the optimal control of degree of CO oxidation to CO2.

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.

A distributed model predictive control approach to cooperative adaptive cruise control of the heterogeneous platoon

2021 ◽  
pp. 095440702110705
Author(s):  
Guangming Nie ◽  
Bo Xie ◽  
Zixu Hao ◽  
Hangwei Hu ◽  
Yantao Tian
Keyword(s):  
Optimal Control ◽  
Model Predictive Control ◽  
Control Problem ◽  
Predictive Control ◽  
Control Algorithm ◽  
Sampling Period ◽  
Distributed Model ◽  
Cruise Control ◽  
Control Approach ◽  
Distributed Model Predictive Control

This paper presents a distributed model predictive control algorithm to solve the cruise control problem of a heterogeneous platoon. Each following vehicle in the platoon can use the communication equipment to receive the information of the leading vehicle and its preceding adjacent one. The vehicles in the platoon are dynamically decoupled and have different dynamic parameters. Each vehicle solves a local optimal control problem independently. The cost function of each vehicle’s local optimal control algorithm is designed with traceability as the control objective, and its asymptotic stability is guaranteed by using the terminal constraint method. In addition, the timestamps of all vehicles in the platoon are synchronous, which means that in each sampling period, a specific vehicle in the platoon cannot obtain the solution results of other vehicles’ local optimal control problems at the current sampling moment. Under this restriction, the constraints that each vehicle needs to meet to realize the platoon’s string stability are also designed. Finally, the simulation results show the effectiveness of the algorithm.

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.

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