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ENGL
2006

An Integral Plus States Adaptive Neural Control of Aerobic Continuous Stirred Tank Reactor

9 years 3 months ago
An Integral Plus States Adaptive Neural Control of Aerobic Continuous Stirred Tank Reactor
A direct adaptive neural network control system with and without integral action term is designed for the general class of continuous biological fermentation processes. The control system consists of a neural identifier and a neural controller, based on the recurrent trainable neural network model. The main objective is to keep the glucose concentration, which is considered as external substrate, close to a constant set-point reference using the dilution rate as manipulating function. It is illustrated by simulations that both adaptive neural control schemes (with and without integral-term) work successfully and exhibit good convergence. However, the control system with integral action is able to compensate a constant offset while the scheme without integration term failed. Results are presented which show a favorable behavior of the neural controller in comparison with existing solutions.
Ieroham S. Baruch, Petia Georgieva, Josefina Barre
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2006
Where ENGL
Authors Ieroham S. Baruch, Petia Georgieva, Josefina Barrera-Cortés
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