Abstract
| Original language | Undefined |
|---|---|
| Pages (from-to) | 1021-1030 |
| Number of pages | 10 |
| Journal | Computers & chemical engineering |
| Volume | 27 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 2003 |
Keywords
- IR-61382
- METIS-214748
Cite this
}
Combining prior knowledge with data-driven modeling of a batch distillation column including start-up. / van Lith, P.F.; van Lith, Pascal F.; Betlem, Bernardus H.L.; Roffel, B.
In: Computers & chemical engineering, Vol. 27, No. 7, 2003, p. 1021-1030.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Combining prior knowledge with data-driven modeling of a batch distillation column including start-up
AU - van Lith, P.F.
AU - van Lith, Pascal F.
AU - Betlem, Bernardus H.L.
AU - Roffel, B.
PY - 2003
Y1 - 2003
N2 - 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.
AB - 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.
KW - IR-61382
KW - METIS-214748
U2 - 10.1016/S0098-1354(03)00067-X
DO - 10.1016/S0098-1354(03)00067-X
M3 - Article
VL - 27
SP - 1021
EP - 1030
JO - Computers & chemical engineering
JF - Computers & chemical engineering
SN - 0098-1354
IS - 7
ER -