PID based on a single artificial neural network algorithm for DC-DC boost converter

Dhaouadi Guiza, Djamel Ounnas, Soufi Youcef, Abdelmalek Bouden


This research focuses on developing a proportional integral derivative controller based on a single artificial neural network (PID-SANN). The proposed control strategy drives the direct current (DC-DC) boost converter output voltage to follow the desired reference value. This controller calculates the PID gains via a learning algorithm based on an artificial single-neuron network, which overcomes the computational complexity of PID gains using analytical methods and automatically adjusts the controller parameters. The developed PID-SANN method offers the boost converter the appropriate duty ratio, which permits controlling the output voltage value despite fluctuations in the resistive load or input voltage. The obtained results confirm that the developed method can successfully surmount the constraints of conventional PID controllers and direct the output voltage of the considered DC-DC converter to follow the required value precisely.


Artificial neural network; DC-DC boost converter; PID controller; PID-SANN method; Self-adaptive

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The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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