Analysis and Comparison of a Non-linear Model and a Model Based on Neural Networks to Estimate the Composition in a Distillation Column

In this paper, the design and validation of a model based on neural networks is presented to estimate online the composition of the light component of a batch distillation column for a binary mixture. The validation is carried out by simulation with real data from a distillation process in an EDF-10...

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Bibliographic Details
Main Authors: Heras-Cervantes, M., Espinosa-Juarez, E., Anzurez-Marin, J., Ramirez-Zavala, S., Tellez-Anguiano, A. C.
Format: Conference Proceeding
Language:eng ; spa
Subjects:
Analytical models
Biological neural networks
Computational modeling
Distillation Column
Distillation equipment
Manganese
Mathematical model
neuronal networks
nonlinear model
Radio frequency
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Summary:In this paper, the design and validation of a model based on neural networks is presented to estimate online the composition of the light component of a batch distillation column for a binary mixture. The validation is carried out by simulation with real data from a distillation process in an EDF-1000 distillation pilot plant for an Ethanol-Water mixture. The obtained results are compared with those of a nonlinear model of a distillation column operating under similar conditions.
ISSN:2573-0770
DOI:10.1109/ROPEC.2018.8661367