A Chemical Reactor Benchmark for Parallel Adaptive Control Using Feedforward Neural Networks

Authors:
Daniel Oliveira Cajueiro;Elder Moreira Hemerly
Affiliations:
-;-
Venue:
SBRN '00 Proceedings of the VI Brazilian Symposium on Neural Networks (SBRN'00)
Year:
2000

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Cited 1

Identification of a typical CSTR using optimal focused time lagged recurrent neural network model with gamma memory filter

Applied Computational Intelligence and Soft Computing

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Abstract

This paper applies a parallel scheme for adaptive control that uses only one neural network to a CSTR (Continuous Stirred Tank Reactor). Convergence of the identification error is investigated by Lyapunov's second method. Using two different techniques carries out the training process of the neural network: backpropagation and extended Kalman filter algorithm.