{"title":"A Comparison of RECCo and FCPFC Controller on Nonlinear Chemical Reactor","authors":"G. Andonovski, E. Lughofer, I. Škrjanc","doi":"10.2316/P.2017.848-049","DOIUrl":null,"url":null,"abstract":"The objective of this paper was to present a performance comparison between a new fuzzy (cloud-based) predictive functional control (FCPFC) and the Robust Evolving Cloud-based controller (RECCo). Both methods use the same type of fuzzy cloud-based system (the same antecedent part). The clouds are used for partitioning the data space and dealing with the non-linearity of the processes. In case of FCPFC the fuzzy cloud-based model is used to identify the process model while the control signal is analytically calculated to minimize some criterion. In case of RECCo algorithm the clouds are used to identify the operating region and the control signal is adapted in online manner. The controllers were tested on a second order nonlinear, locally oscillating, chemical process CSTR (Continuous Stirred Tank Reactor). The performance and control effort of the methods were compared according to several criteria. The results show that the proposed controller FCPFC has slightly faster response but longer settling time than the RECCo controller.","PeriodicalId":49801,"journal":{"name":"Modeling Identification and Control","volume":"35 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Modeling Identification and Control","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.2316/P.2017.848-049","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 2
Abstract
The objective of this paper was to present a performance comparison between a new fuzzy (cloud-based) predictive functional control (FCPFC) and the Robust Evolving Cloud-based controller (RECCo). Both methods use the same type of fuzzy cloud-based system (the same antecedent part). The clouds are used for partitioning the data space and dealing with the non-linearity of the processes. In case of FCPFC the fuzzy cloud-based model is used to identify the process model while the control signal is analytically calculated to minimize some criterion. In case of RECCo algorithm the clouds are used to identify the operating region and the control signal is adapted in online manner. The controllers were tested on a second order nonlinear, locally oscillating, chemical process CSTR (Continuous Stirred Tank Reactor). The performance and control effort of the methods were compared according to several criteria. The results show that the proposed controller FCPFC has slightly faster response but longer settling time than the RECCo controller.
期刊介绍:
The aim of MIC is to present Nordic research activities in the field of modeling, identification and control to the international scientific community. Historically, the articles published in MIC presented the results of research carried out in Norway, or sponsored primarily by a Norwegian institution. Since 2009 the journal also accepts papers from the other Nordic countries.