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

Daniel Oliveira CajueiroElder Moreira Hemerly

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.

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Biblioteca Digital Brasileira de Computação - Contato:
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