ON A METHOD OF CONTROLLING THE HEATER BY USING NEURAL NETWORKS
S. S. Abdurakipov, E. B. Butakov
Kutateladze Institute of Thermophysics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia
Keywords: control systems, PID controller, machine learning, recurrent neural network, anomaly detection
Abstract
The paper studies the possibility of using a long short-term memory (LSTM) neural network to simulate the operation of a PID controller. A PID regulator has been implemented to control a heater with a temperature sensor by using the Arduino framework. An LSTM model trained on the controller data has been developed. It is shown that the neural network model quite accurately reproduces the regulator operation and can completely replace it. In addition, the applicability of this model as a detector of abnormal operation of the PID controller is shown.
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