Combining prior knowledge with data driven modeling of a batch distillation column including start-up
Autor: | van Lith, P.F., van Lith, Pascal F., Betlem, Bernardus H.L., Roffel, B. |
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Přispěvatelé: | Faculty of Science and Technology, Chemical Technology, Stratingh Institute of Chemistry |
Jazyk: | angličtina |
Rok vydání: | 2003 |
Předmět: |
Structure (mathematical logic)
Batch distillation Computer science General Chemical Engineering hybrid modeling batch distillation Process (computing) Control engineering Column (database) Fuzzy logic METIS-214748 Computer Science Applications Data-driven System dynamics dynamic modeling IR-61382 A priori and a posteriori OPERATION fuzzy logic |
Zdroj: | Computers & chemical engineering, 27(7), 1021-1030. Elsevier Computers and Chemical Engineering, 27(7), 1021-1030. PERGAMON-ELSEVIER SCIENCE LTD |
ISSN: | 0098-1354 |
Popis: | This paper presents the development of a simple model which describes the product quality and production over time of an experimental batch distillation column, including start-up. The model structure is based on a simple physical framework, which is augmented with fuzzy logic. This provides a way to use prior knowledge about the dynamics, which have a general validity, while additional information about the specific column behavior is derived from measured process data. The model framework is applicable for a wide range of columns operating under a certain control policy. The model framework for the particular column under study makes a priori assumptions about the specific behavior superfluous. In addition, a detailed description of the internal dynamics is not required, which reduces modeling effort. Three different hybrid model structures are compared; the model that uses the available sources of information most effectively can be used to simulate production including part of the start-up by applying constant quality control. (C) 2003 Elsevier Science Ltd. All rights reserved. |
Databáze: | OpenAIRE |
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