DocumentCode
2990110
Title
Recurrent Neural Networks Biomass Observer for Anaerobic Processes
Author
Urrego-Patarroyo, D.A. ; Sanchez, E.N. ; Carlos-Hernandez, S. ; Beteau, J.F.
Author_Institution
CINVESTAV del IPN, Unidad Guadalajara, Zapopan
fYear
2008
fDate
3-5 Sept. 2008
Firstpage
183
Lastpage
188
Abstract
In this paper, a recurrent neural networks observer for anaerobic processes is proposed; the main objective is to estimate biomass, in a completely stirred tank reactor. The neural network is trained with an extended Kalman filter algorithm. The applicability of the proposed observer is verified via simulations.
Keywords
Kalman filters; chemical engineering computing; chemical reactors; nonlinear filters; recurrent neural nets; anaerobic processes; biomass estimation; completely stirred tank reactor; extended Kalman filter algorithm; neural network training; recurrent neural networks biomass observer; Biomass; Continuous-stirred tank reactor; Control systems; Inductors; Intelligent control; Microorganisms; Neural networks; Observers; Recurrent neural networks; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 2008. ISIC 2008. IEEE International Symposium on
Conference_Location
San Antonio, TX
ISSN
2158-9860
Print_ISBN
978-1-4244-2224-1
Electronic_ISBN
2158-9860
Type
conf
DOI
10.1109/ISIC.2008.4635946
Filename
4635946
Link To Document