An adaptive real-time grey-box model for advanced control and operations in WRRFs

Grey-box models, which combine the explanatory power of first-principle models with the ability to detect subtle patterns from data, are gaining increasing attention in wastewater sectors. Intuitive, simple structured but fit-for-purpose grey-box models that capture time-varying dynamics by adaptive...

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Autores principales:	Cheng Yang, Peter Seiler, Evangelia Belia, Glen T. Daigger
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	activated sludge extended kalman filter grey-box model parameter estimation sumo Environmental technology. Sanitary engineering TD1-1066
Acceso en línea:	https://doaj.org/article/8d9b3b0bde574fc299d9e8cf26478c61
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id	oai:doaj.org-article:8d9b3b0bde574fc299d9e8cf26478c61
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spelling	oai:doaj.org-article:8d9b3b0bde574fc299d9e8cf26478c612021-11-23T18:40:55ZAn adaptive real-time grey-box model for advanced control and operations in WRRFs0273-12231996-973210.2166/wst.2021.408https://doaj.org/article/8d9b3b0bde574fc299d9e8cf26478c612021-11-01T00:00:00Zhttp://wst.iwaponline.com/content/84/9/2353https://doaj.org/toc/0273-1223https://doaj.org/toc/1996-9732Grey-box models, which combine the explanatory power of first-principle models with the ability to detect subtle patterns from data, are gaining increasing attention in wastewater sectors. Intuitive, simple structured but fit-for-purpose grey-box models that capture time-varying dynamics by adaptively estimating parameters are desired for process optimization and control. As an example, this study presents the identification of such a grey-box model structure and its further use by an extended Kalman filter (EKF), for the estimation of the nitrification capacity and ammonia concentrations of a typical Modified Ludzack-Ettinger (MLE) process. The EKF was implemented and evaluated in real time by interfacing Python with SUMO (Dynamita™), a widely used commercial process simulator. The EKF was able to accurately estimate the ammonia concentrations in multiple tanks when given only the concentration in one of them. In addition, the nitrification capacity of the system could be tracked in real time by the EKF, which provides intuitive information for facility managers and operators to monitor and operate the system. Finally, the realization of EKF is critical to the development of future advance control, for instance, model predictive control. HIGHLIGHTS The development of an adaptive real-time grey-box model with intuitive information is presented.; The need of model adaptivity was identified and fulfilled by the extended Kalman filter.; The extracted real-time intuitive information will help WRRFs staff in operations and management.; Model structure simplicity and development pathway encourages applications for other processes.;Cheng YangPeter SeilerEvangelia BeliaGlen T. DaiggerIWA Publishingarticleactivated sludgeextended kalman filtergrey-box modelparameter estimationsumoEnvironmental technology. Sanitary engineeringTD1-1066ENWater Science and Technology, Vol 84, Iss 9, Pp 2353-2365 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	activated sludge extended kalman filter grey-box model parameter estimation sumo Environmental technology. Sanitary engineering TD1-1066
spellingShingle	activated sludge extended kalman filter grey-box model parameter estimation sumo Environmental technology. Sanitary engineering TD1-1066 Cheng Yang Peter Seiler Evangelia Belia Glen T. Daigger An adaptive real-time grey-box model for advanced control and operations in WRRFs
description	Grey-box models, which combine the explanatory power of first-principle models with the ability to detect subtle patterns from data, are gaining increasing attention in wastewater sectors. Intuitive, simple structured but fit-for-purpose grey-box models that capture time-varying dynamics by adaptively estimating parameters are desired for process optimization and control. As an example, this study presents the identification of such a grey-box model structure and its further use by an extended Kalman filter (EKF), for the estimation of the nitrification capacity and ammonia concentrations of a typical Modified Ludzack-Ettinger (MLE) process. The EKF was implemented and evaluated in real time by interfacing Python with SUMO (Dynamita™), a widely used commercial process simulator. The EKF was able to accurately estimate the ammonia concentrations in multiple tanks when given only the concentration in one of them. In addition, the nitrification capacity of the system could be tracked in real time by the EKF, which provides intuitive information for facility managers and operators to monitor and operate the system. Finally, the realization of EKF is critical to the development of future advance control, for instance, model predictive control. HIGHLIGHTS The development of an adaptive real-time grey-box model with intuitive information is presented.; The need of model adaptivity was identified and fulfilled by the extended Kalman filter.; The extracted real-time intuitive information will help WRRFs staff in operations and management.; Model structure simplicity and development pathway encourages applications for other processes.;
format	article
author	Cheng Yang Peter Seiler Evangelia Belia Glen T. Daigger
author_facet	Cheng Yang Peter Seiler Evangelia Belia Glen T. Daigger
author_sort	Cheng Yang
title	An adaptive real-time grey-box model for advanced control and operations in WRRFs
title_short	An adaptive real-time grey-box model for advanced control and operations in WRRFs
title_full	An adaptive real-time grey-box model for advanced control and operations in WRRFs
title_fullStr	An adaptive real-time grey-box model for advanced control and operations in WRRFs
title_full_unstemmed	An adaptive real-time grey-box model for advanced control and operations in WRRFs
title_sort	adaptive real-time grey-box model for advanced control and operations in wrrfs
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/8d9b3b0bde574fc299d9e8cf26478c61
work_keys_str_mv	AT chengyang anadaptiverealtimegreyboxmodelforadvancedcontrolandoperationsinwrrfs AT peterseiler anadaptiverealtimegreyboxmodelforadvancedcontrolandoperationsinwrrfs AT evangeliabelia anadaptiverealtimegreyboxmodelforadvancedcontrolandoperationsinwrrfs AT glentdaigger anadaptiverealtimegreyboxmodelforadvancedcontrolandoperationsinwrrfs AT chengyang adaptiverealtimegreyboxmodelforadvancedcontrolandoperationsinwrrfs AT peterseiler adaptiverealtimegreyboxmodelforadvancedcontrolandoperationsinwrrfs AT evangeliabelia adaptiverealtimegreyboxmodelforadvancedcontrolandoperationsinwrrfs AT glentdaigger adaptiverealtimegreyboxmodelforadvancedcontrolandoperationsinwrrfs
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An adaptive real-time grey-box model for advanced control and operations in WRRFs

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