A HYBRID NEURAL MODEL FOR THE OPTIMIZATION OF FED-BATCH FERMENTATIONS
In this work a hybrid neural modelling methodology, which combines mass balance equations with functional link networks (FLNs), used to represent kinetic rates, is developed for bioprocesses. The simple structure of the FLNs allows the easy and rapid estimation of network weights and, consequently, the use of the hybrid model in an adaptive form. As the proposed model is able to adjust to kinetic and environmental changes, it is suitable for use in the development of optimization strategies for fed-batch bioreactors. The proposed methodology is used to model the processes for penicillin and ethanol production, and the development of an adaptive optimal control scheme is discussed using ethanol fermentation as an example.
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Digital revista |
| Language: | English |
| Published: |
Brazilian Society of Chemical Engineering
1999
|
| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-66321999000100006 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|