This paper explores BLDC motor control using MATLAB Simulink, focusing on AI tuned PID and fractional PID controllers for closed-loop speed regulation and direction . It involves designing a feedback system comprising sensor feedback, controller, and BLDC motor model. Through iterative tuning, optimal controller parameters are determined for enhanced performance. Simulations were carried out to evaluate response characteristics, stability, and robustness across varying conditions. Experimental validation though hardware-in-the-loop experiments corroborates simulation findings. Performance metrics, including speed accuracy and disturbance rejection, are analyzed to compare the effectiveness of PID and fractional PID controllers. This work provides insights into advanced control techniques for BLDC motors, aiding in the selection of suitable strategies for real-world applications.