PI CONTROLLER WITH NEURAL NETWORK ADJUSTMENT FOR SPEED REGULATION IN BRUSHLESS DIRECT CURRENT MOTOR

Autor:	Hulusi Hulusi Karaca, Taner Dindar, Yasin Bektaş
Rok vydání:	2018
Předmět:	Artificial neural network Computer science Control theory PID controller General Medicine DC motor
Zdroj:	Applied Researches in Technics, Technologies and Education. 6:16-29
ISSN:	1314-8796 1314-8788
DOI:	10.15547/artte.2018.01.003
Popis:	Brushless DC motor (BLDCM) has been widely used in many different fields such as high efficiency and dynamic response and high speed range in recent years. Since the BLDC motor driver does not behave, it is complex to control it via the proportional-integral (PI) controller. In this article, the mathematical model of the BLDC motor and artificial neural network algorithm is derived to make the BLDC motor control. On the proposed drive, the controller synchronizes quickly with speed, learning the motor speed to follow and load quickly. The effectiveness of the proposed method is demonstrated by the model developed in MATLAB / Simulink. The simulation results show that the proposed artificial neural network controller provides a significant improvement in control performance compared to the PI controller for both control reference speed changes and load changes.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::90ff6b82b7af77ce79ab7b5e1d2044ea https://doi.org/10.15547/artte.2018.01.003 Zobrazit plný text záznamu