INTELLIGENT SPEED CONTROL OF BLDC MOTOR USING ADAPTIVE CONTROL ALGORITHMS

Abstract

Brushless DC (BLDC) motors are widely used in industrial automation, electric vehicles, robotics, and consumer electronics due to their high efficiency, high torque-to-weight ratio, and low maintenance requirements. However, achieving precise and robust speed control under varying load and parameter uncertainties remains a significant challenge. Conventional proportional–integral (PI) controllers often fail to provide optimal performance under dynamic operating conditions. This paper presents an intelligent speed control approach for BLDC motors using adaptive control algorithms. The proposed system dynamically adjusts control parameters in response to load variations and system nonlinearities, ensuring improved speed regulation and stability. MATLAB/Simulink-based simulations demonstrate enhanced transient response, reduced steady-state error, and superior robustness compared to traditional control methods, validating the effectiveness of adaptive control for BLDC motor applications.