{"title":"Implementation of model predictive control in a programmable logic controller","authors":"Yurii Mariiash, O. Stepanets","doi":"10.31713/mcit.2023.078","DOIUrl":null,"url":null,"abstract":"The article is aimed at the development of modern automatic control systems, which should provide high-performance indicators in the conditions of variable operating modes of industrial equipment due to effective control structures and algorithms. The purpose of the study is to reduce the cost of the basic oxygen furnace steel, which is a consequence of the increase in the share of scrap metal due to the enhanced post-burning of CO to CO2 in the cavity, by optimal controlling the duty mode parameters using model-predictive control. The blowing mode of the basic oxygen furnace was considered as a technological object of control, and the problem of controlling blowing parameters in conditions of non-stationarity of the rate of metal decarburization was analyzed. The use of a model-predictive controller made it possible to improve the quality of control for the oxygen flow circuit by 39% and the maximum dynamic deviation of the CO2 content in the gases was reduced by 16.5% compared to the PID control. The implementation of a software-hardware control system using model-predictive control based on a programmable logic controller is considered.","PeriodicalId":281857,"journal":{"name":"Modeling Control and Information Technologies","volume":"118 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Modeling Control and Information Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31713/mcit.2023.078","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The article is aimed at the development of modern automatic control systems, which should provide high-performance indicators in the conditions of variable operating modes of industrial equipment due to effective control structures and algorithms. The purpose of the study is to reduce the cost of the basic oxygen furnace steel, which is a consequence of the increase in the share of scrap metal due to the enhanced post-burning of CO to CO2 in the cavity, by optimal controlling the duty mode parameters using model-predictive control. The blowing mode of the basic oxygen furnace was considered as a technological object of control, and the problem of controlling blowing parameters in conditions of non-stationarity of the rate of metal decarburization was analyzed. The use of a model-predictive controller made it possible to improve the quality of control for the oxygen flow circuit by 39% and the maximum dynamic deviation of the CO2 content in the gases was reduced by 16.5% compared to the PID control. The implementation of a software-hardware control system using model-predictive control based on a programmable logic controller is considered.
文章旨在开发现代自动控制系统,通过有效的控制结构和算法,在工业设备运行模式多变的条件下提供高性能指标。该研究的目的是通过使用模型预测控制对工作模式参数进行优化控制,降低碱性氧气炉炼钢的成本,该成本是由于加强了炉腔内 CO 到 CO2 的后燃烧而导致废金属比例增加的结果。基本氧气炉的鼓风模式被视为一个技术控制对象,并分析了在金属脱碳率非稳定条件下的鼓风参数控制问题。与 PID 控制相比,模型预测控制器的使用使氧气流量回路的控制质量提高了 39%,气体中二氧化碳含量的最大动态偏差降低了 16.5%。该研究考虑了在可编程逻辑控制器的基础上使用模型预测控制的软硬件控制系统的实施。