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
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;
Conference_Titel :
Intelligent Control, 2008. ISIC 2008. IEEE International Symposium on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-2224-1
Electronic_ISBN :
2158-9860
DOI :
10.1109/ISIC.2008.4635946
