Modeling and control of a packed distillation column using artificial neural networks

Artificial neural networks, because they are nets of basis functions, can provide good empirical models of complex nonlinear processes that are useful for many purposes including process control. The modelling of a packed distillation column described here provides an interesting example of complex...

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Bibliographic Details
Published in:Computers & chemical engineering 1995-10, Vol.19 (10), p.1077-1088
Main Authors: Macmurray, J.C., Himmelblau, D.M.
Format: Article
Language:English
Subjects:
Applied sciences
Chemical engineering
Distillation
Exact sciences and technology
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Summary:Artificial neural networks, because they are nets of basis functions, can provide good empirical models of complex nonlinear processes that are useful for many purposes including process control. The modelling of a packed distillation column described here provides an interesting example of complex modeling because the column exhibits a change in the sign of the gain under various operating conditions. We show how artificial neural networks can model the column, and demonstrate that the network model is as good or better than a simplified first principles model when used for model predictive control.
ISSN:0098-1354
1873-4375
DOI:10.1016/0098-1354(94)00098-9