Синтез модельно-прогнозуючого регулятора режиму дуття киснево-конвертерного процесу

Olexandr Stepanets, Yurii Mariiash
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Abstract

The purpose of the research was to find a solution for a decrease in the cost price of the basic oxygen furnace steel. It is conditioned by an increase in the scrap metal portion due to an increase in the СО to CO2 afterburn degree in the basic oxygen furnace cavity according to the optimal model predictive control of the parameters of the blowing mode. The optimal parameter control system was synthesized for the blowing mode of the oxygen-converter melting on the basis of the feedback based on the model-predictive control using the linear-quadratic functional and it enabled a simultaneous control of the blowing intensity and the lance position  when programmatically changing the task for the oxygen consumption and CO2 content improving also the control quality and energy saving during the melting process due to an increased afterburn degree during the CO to CO2 conversion that is a consequence of an increased portion of the scrap metal. Closed CO to CO2 afterburn degree control systems were improved by the synthesis of the model-predictive controller taking into consideration process limitations imposed on the shifting rate of controlling mechanisms, improving thus the process control quality in the case of the limitations. The suggested solution enables certain process control quality improvement under the conditions of process limitations. A comparative investigation of the operation of the model – predictive controller and combined control system with PID–controllers showed that the obtained transition processes of the automatic control of the blowing mode for the basic oxygen furnace melting using the automatic model-predictive controller  provided ISE values for the oxygen consumption loop equal to 5577 and the CO2 content equal to 43 in basic oxygen furnace gases with a maximum dynamic deviation of the CO2 content in converter gases equal to 0.95 %. The use of the model-predictive controller allowed us to improve the control quality for the oxygen consumption loop by a factor of 1.63 CO2 and by a factor of 32.5 for the CO2 content control loop in converter gases. A maximum dynamic deviation of the CO2 content in converter gases was reduced by 16.55 % in comparison to that in the combined control system equipped with PID-controllers.
研究的目的是寻找降低氧基炉钢成本价的解决方案。根据吹制方式参数的最优模型预测控制,以基本氧炉腔内СО→CO2加力度增加导致废金属部分增加为条件。最优参数控制系统合成的吹模式氧气转融的基础上,使用线性二次反馈基于模型预测控制的功能和它使同时控制吹强度和兰斯位置当以编程方式更改任务的耗氧量和二氧化碳含量也提高控制质量和节能在融化过程中由于增加了烟火特效学位在CO到CO2的转化过程中,这是废金属部分增加的结果。考虑到控制机构变速速率的过程限制,通过模型预测控制器的综合改进了封闭式CO - CO2加力度控制系统,从而提高了在这种限制情况下的过程控制质量。建议的解决方案能够在工艺限制条件下实现一定的工艺控制质量改进。比较的调查模型,预测控制器的操作和控制系统相结合意义表明,获得的过渡过程的自动控制氧气顶吹转炉吹模式融化使用提供的自动模型预测控制器伊势值耗氧量循环等于5577和二氧化碳含量等于43在氧气顶吹转炉气体二氧化碳含量的最大动态偏差转换器气体等于0.95%。模型预测控制器的使用使我们能够将氧气消耗回路的控制质量提高1.63 CO2,并将转炉气体中CO2含量控制回路的控制质量提高32.5。与采用pid控制器的组合控制系统相比,转炉气体中CO2含量的最大动态偏差降低了16.55%。
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