Neural Network Based Explicit MPC for Chemical Reactor Control

In this paper, we show the implementation of deep neural networks applied in process control. In our approach, we based the training of the neural network on model predictive control. Model predictive control is popular for its ability to be tuned by the weighting matrices and by the fact that it re...

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Veröffentlicht in:	arXiv.org 2019-12
Hauptverfasser:	Kiš, Karol, Klaučo, Martin
Format:	Artikel
Sprache:	eng
Schlagworte:	Chemical reactions Chemical reactors Computer simulation Continuously stirred tank reactors Neural networks Organic chemistry Predictive control Trajectory control Weighting
Online-Zugang:	Volltext
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