Abstract
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.
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