{"title":"Estimation Based Control Strategies for an Aerobic Bioprocess","authors":"F. Stîngă, E. Petre","doi":"10.1109/ICSTCC.2018.8540684","DOIUrl":null,"url":null,"abstract":"This paper presents two estimation based control strategies for an aerobic process used in wastewater biological treatment carried out inside a CSTR (Continuous Stirred Tank Reactor). Our control objective is to keep the effluent pollutant concentration at a desired low level, and also to ensure that the dissolved oxygen concentration follows some imposed references. Therefore we propose two new control schemes for robust-adaptive and model predictive control, taking into account the Bayesian based weighted values of the state’s estimations provided by an interval observer and a parameter estimator of the unknown growth rate. A comparison of the effectiveness of the two approaches is illustrated by numerical simulations performed under different conditions related to some degree of uncertainness of a continuous wastewater treatment bioprocess.","PeriodicalId":308427,"journal":{"name":"2018 22nd International Conference on System Theory, Control and Computing (ICSTCC)","volume":"R-28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 22nd International Conference on System Theory, Control and Computing (ICSTCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSTCC.2018.8540684","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper presents two estimation based control strategies for an aerobic process used in wastewater biological treatment carried out inside a CSTR (Continuous Stirred Tank Reactor). Our control objective is to keep the effluent pollutant concentration at a desired low level, and also to ensure that the dissolved oxygen concentration follows some imposed references. Therefore we propose two new control schemes for robust-adaptive and model predictive control, taking into account the Bayesian based weighted values of the state’s estimations provided by an interval observer and a parameter estimator of the unknown growth rate. A comparison of the effectiveness of the two approaches is illustrated by numerical simulations performed under different conditions related to some degree of uncertainness of a continuous wastewater treatment bioprocess.