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Controller tunning for flow-through heater using artificial intelligence based on digital twin with recurrent neural networks
Michał Frątczak 1
,
 
Krzysztof Żyła 1
,
 
Piotr Łaszczyk 1
 
 
 
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Silesian university of Technology, Akademicka 16, 44-100 Gliwice, Poland
 
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Autor do korespondencji
Michał Frątczak   

Silesian university of Technology, Akademicka 16, 44-100 Gliwice, Poland
 
 
 
SŁOWA KLUCZOWE
neural network
process modelling
LSTM
RNN
flow-trough heater
 
DZIEDZINY
 
STRESZCZENIE
The presented research results are related to the modelling and simulation of technological processes using recurrent neural networks (RNN). This paper presents the application of such modelling technique for a flow-through heater. The structure of the RNN is presented and the correctness of the obtained modelling results is verified. The application of such a model for the classical PI algorithm controller tuning is presented. The results were compared with the popular PI algorithm tuning rule (Chien-Hrones-Reswick). The advantage of the proposed approach to tuning controllers over traditional methods was pointed out.
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