부산대학교 도서관

Brushless Direct Current (BLDC) motors are widely used in electromobility and industrial robots. BLDC motors are essential in many production applications. However, they encounter significant challenges when it comes to executing control of speed. Due to their simplicity, speed controllers are often designed using Proportional Integral (PI) regulation. The saturation of standard PI control makes the system unreliable, hence an online radial basis function (RBF) neural network is proposed. The paper compares and evaluates the speed response of two regulators under a reference speed of 3000 RPM. The purpose is to examine and contrast the performance of these regulators in regulating the speed of the system. In comparison to the traditional PI controller, the presented controller demonstrates superior characteristics such as lower overshoot, improved response speed and greater anti-disturbance capability. The studies are conducted in MATLAB/Simulink.