DocumentCode :
1911159
Title :
An adaptive neural control of a fed-batch fermentation processes
Author :
Baruch, Ieroham S. ; Cortes, Josefina Barrera ; Medina, Jenaro Perez ; Pelez, L.A.H.
Author_Institution :
Bulgarian Acad. of Sci., Sofia, Bulgaria
Volume :
2
fYear :
2003
fDate :
23-25 June 2003
Firstpage :
808
Abstract :
A nonlinear mathematical model of a feed-batch fermentation process of Bacillus thuringiensis (Bt.) is derived and a theorem proof of the existence of positive solution of the obtained model is done. The obtained model is validated by experimental data. An identification and adaptive neural control scheme of the system, represented by a neural identifier and a neural controller, based on the recurrent trainable neural network model, is proposed. The applicability of the proposed adaptive control scheme is confirmed by simulation results, which exhibits a good convergence.
Keywords :
adaptive control; backpropagation; batch processing (industrial); fermentation; identification; neurocontrollers; process control; recurrent neural nets; Bacillus thuringiensis; adaptive neural control; dynamic backpropagation; fed-batch fermentation processes; neural controller; neural identifier; nonlinear control systems; nonlinear mathematical model; recurrent trainable neural network model; systems identification scheme; Adaptive control; Artificial neural networks; Backpropagation; Control system synthesis; Convergence; Mathematical model; Neural networks; Power system modeling; Programmable control; Recurrent neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Applications, 2003. CCA 2003. Proceedings of 2003 IEEE Conference on
Print_ISBN :
0-7803-7729-X
Type :
conf
DOI :
10.1109/CCA.2003.1223113
Filename :
1223113
Link To Document :
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