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