On-Line Nonlinear Dynamic Data Reconciliation Using Extended Kalman Filtering: Application to a Distillation Column and a CSTR
Extended Kalman Filtering (EKF) is a nonlinear dynamic data reconciliation (NDDR) method. One of its main advantages is its suitability for on-line applications. This paper presents an on-line NDDR method using EKF. It is implemented for two case studies, temperature measurements of a distillation c...
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| Format: | Article |
| Language: | English |
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Iranian Institute of Research and Development in Chemical Industries (IRDCI)-ACECR
2009-09-01
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| Series: | Iranian Journal of Chemistry & Chemical Engineering |
| Subjects: | |
| Online Access: | http://www.ijcce.ac.ir/article_6841_09e918c087540f60b39086839eb026a4.pdf |
| _version_ | 1818533394570543104 |
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| author | Ali Farzi Arjomand Mehrabani-Zeinabad Ramin Bozorgmehry Boozarjomehry |
| author_facet | Ali Farzi Arjomand Mehrabani-Zeinabad Ramin Bozorgmehry Boozarjomehry |
| author_sort | Ali Farzi |
| collection | DOAJ |
| description | Extended Kalman Filtering (EKF) is a nonlinear dynamic data reconciliation (NDDR) method. One of its main advantages is its suitability for on-line applications. This paper presents an on-line NDDR method using EKF. It is implemented for two case studies, temperature measurements of a distillation column and concentration measurements of a CSTR. In each time step, random numbers with zero mean and specified variance were added to simulated results by a random number generator. The generated data are transferred on-line to a developed data reconciliation software. The software performs NDDR on received data using EKF method. Comparison of data reconciliation results with simulated measurements and true values demonstrates a high reduction in measurement errors, while benefits high speed data reconciliation process. |
| first_indexed | 2024-12-11T17:58:07Z |
| format | Article |
| id | doaj.art-6109d158e99048b9aeb484f421d8e05c |
| institution | Directory Open Access Journal |
| issn | 1021-9986 1021-9986 |
| language | English |
| last_indexed | 2024-12-11T17:58:07Z |
| publishDate | 2009-09-01 |
| publisher | Iranian Institute of Research and Development in Chemical Industries (IRDCI)-ACECR |
| record_format | Article |
| series | Iranian Journal of Chemistry & Chemical Engineering |
| spelling | doaj.art-6109d158e99048b9aeb484f421d8e05c2022-12-22T00:55:59ZengIranian Institute of Research and Development in Chemical Industries (IRDCI)-ACECRIranian Journal of Chemistry & Chemical Engineering1021-99861021-99862009-09-012831146841On-Line Nonlinear Dynamic Data Reconciliation Using Extended Kalman Filtering: Application to a Distillation Column and a CSTRAli Farzi0Arjomand Mehrabani-Zeinabad1Ramin Bozorgmehry Boozarjomehry2Department of Chemical Engineering, Faculty of Chemistry, University of Tabriz, Tabriz, I.R. IRANDepartment of Chemical Engineering, Isfahan University of Technology, 84156-83111 Isfahan, I.R. IRANDepartment of Chemical Engineering and Petroleum, Sharif University of Technology, Tehran, I.R. IRANExtended Kalman Filtering (EKF) is a nonlinear dynamic data reconciliation (NDDR) method. One of its main advantages is its suitability for on-line applications. This paper presents an on-line NDDR method using EKF. It is implemented for two case studies, temperature measurements of a distillation column and concentration measurements of a CSTR. In each time step, random numbers with zero mean and specified variance were added to simulated results by a random number generator. The generated data are transferred on-line to a developed data reconciliation software. The software performs NDDR on received data using EKF method. Comparison of data reconciliation results with simulated measurements and true values demonstrates a high reduction in measurement errors, while benefits high speed data reconciliation process.http://www.ijcce.ac.ir/article_6841_09e918c087540f60b39086839eb026a4.pdfdata reconciliationnonlinear dynamic data reconciliationextended kalman filteringdistillation columncstrobject-oriented programming |
| spellingShingle | Ali Farzi Arjomand Mehrabani-Zeinabad Ramin Bozorgmehry Boozarjomehry On-Line Nonlinear Dynamic Data Reconciliation Using Extended Kalman Filtering: Application to a Distillation Column and a CSTR Iranian Journal of Chemistry & Chemical Engineering data reconciliation nonlinear dynamic data reconciliation extended kalman filtering distillation column cstr object-oriented programming |
| title | On-Line Nonlinear Dynamic Data Reconciliation Using Extended Kalman Filtering: Application to a Distillation Column and a CSTR |
| title_full | On-Line Nonlinear Dynamic Data Reconciliation Using Extended Kalman Filtering: Application to a Distillation Column and a CSTR |
| title_fullStr | On-Line Nonlinear Dynamic Data Reconciliation Using Extended Kalman Filtering: Application to a Distillation Column and a CSTR |
| title_full_unstemmed | On-Line Nonlinear Dynamic Data Reconciliation Using Extended Kalman Filtering: Application to a Distillation Column and a CSTR |
| title_short | On-Line Nonlinear Dynamic Data Reconciliation Using Extended Kalman Filtering: Application to a Distillation Column and a CSTR |
| title_sort | on line nonlinear dynamic data reconciliation using extended kalman filtering application to a distillation column and a cstr |
| topic | data reconciliation nonlinear dynamic data reconciliation extended kalman filtering distillation column cstr object-oriented programming |
| url | http://www.ijcce.ac.ir/article_6841_09e918c087540f60b39086839eb026a4.pdf |
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