Direct Adaptive Soft Computing Neural Control of a Continuous Bioprocess via Second Order Learning

Authors:
Ieroham Baruch;Carlos-Roman Mariaca-Gaspar;Josefina Barrera-Cortes
Affiliations:
Department of Automatic Control, CINVESTAV-IPN, Mexico City, Mexico 07360;Department of Automatic Control, CINVESTAV-IPN, Mexico City, Mexico 07360;Department of Biotechnology and Bioengineering, CINVESTAV-IPN, Mexico City, Mexico 07360
Venue:
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
Year:
2009

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Abstract

This paper proposes a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) second order learning algorithm capable to estimate parameters and states of highly nonlinear bioprocess in a noisy environment. The proposed KFRNN identifier, learned by the Backpropagation and L-M learning algorithm, was incorporated in a direct adaptive neural control scheme. The proposed control scheme was applied for real-time soft computing identification and control of a continuous stirred tank bioreactor model, where fast convergence, noise filtering and low mean squared error of reference tracking were achieved.