Open AccessPI CONTROLLER WITH NEURAL NETWORK ADJUSTMENT FOR SPEED REGULATION IN BRUSHLESS DIRECT CURRENT MOTOR
Author(s) -
Yasin Bektaş,
Hulusi Karaca,
Taner Dindar
Publication year - 2018
Publication title -
applied researches in technics, technologies and education
Language(s) - English
Resource type - Journals
eISSN - 1314-8796
pISSN - 1314-8788
DOI - 10.15547/artte.2018.01.003
Subject(s) - control theory (sociology) , electronic speed control , artificial neural network , controller (irrigation) , computer science , pid controller , dc motor , matlab , control engineering , motor controller , control (management) , artificial intelligence , engineering , temperature control , physics , agronomy , electrical engineering , biology , power (physics) , quantum mechanics , operating system
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.