Bio-ethanol production optimization using ACD with ESN critic

In the present paper on-line action-dependent heuristic neuro-dynamic programming was applied for optimization of a complex nonlinear production process. The approach is based on recurrent neural network architecture - Echo state network (ESN) - as critic network within the frame of adaptive critic...

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Bibliographic Details
Published in2011 International Symposium on Innovations in Intelligent Systems and Applications pp. 606 - 610
Main Authors Iliev, V., Kostov, G., Stoycheva, J., Koprinkova-Hristova, P., Angelov, M., Popova, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2011
Subjects
action dependent heuristic dynamic programming
adaptive critic design
Artificial neural networks
bio-ethanol production process
Biomass
echo state network
Ethanol
Optimization
Productivity
Training
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Summary:In the present paper on-line action-dependent heuristic neuro-dynamic programming was applied for optimization of a complex nonlinear production process. The approach is based on recurrent neural network architecture - Echo state network (ESN) - as critic network within the frame of adaptive critic design (ACD) scheme. The subject for optimization is bio-ethanol fermentation. The aim was to increase process productivity defining optimal dilution rate profile. The obtained by simulations results are good basis for further experimental investigations.
ISBN:9781612849195
1612849199
DOI:10.1109/INISTA.2011.5946167