{"title":"Development of a Neuro-fuzzy Model of a Polymerizer Reactor","authors":"A. G. Lopatin, B. A. Brykov, A. Lukina","doi":"10.1109/ICIEAM54945.2022.9787112","DOIUrl":null,"url":null,"abstract":"The article proposes an universal algorithm for the synthesis of fuzzy models of industrial control objects using adaptive neuro-fuzzy inference system. A typical polymerizer reactor is used as an example to create a model. The stages of synthesis a fuzzy model, the initial conditions of modeling, the block diagram of the model and the results of simulation modeling are given. A good convergence of the results of the fuzzy model and the initial data is shown. It is shown that the presented algorithm for the synthesis of fuzzy models can be adapted to any control object such as a reactor.","PeriodicalId":128083,"journal":{"name":"2022 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEAM54945.2022.9787112","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 proposes an universal algorithm for the synthesis of fuzzy models of industrial control objects using adaptive neuro-fuzzy inference system. A typical polymerizer reactor is used as an example to create a model. The stages of synthesis a fuzzy model, the initial conditions of modeling, the block diagram of the model and the results of simulation modeling are given. A good convergence of the results of the fuzzy model and the initial data is shown. It is shown that the presented algorithm for the synthesis of fuzzy models can be adapted to any control object such as a reactor.
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