Bald eagle search algorithm based PI control method for speed control of BLDC motor drives

Optimizing the proportional-integral (PI) controllers in brushless direct current (BLDC) motors can improve performance by minimizing the rise time, settling time, and steady-state error. Therefore, a new strategy for speed control for BLDC motors was presented using the bald eagle search (BES) algorithm for optimizing the PI controller. The main objective of this research was to enhance the dynamic performance of the BLDC motor with high efficiency and low steady-state error under load saturation and different operating conditions. The novel speed controller based on the BES–PI methodology is suggested to optimize the controller parameters without the necessity of using the trial-and-error technique. Simulations of the BLDC motor governed by hysteresis current control (HCC) were conducted through the MATLAB/Simulink environment. The obtained results were compared with those achieved using particle swarm optimization (PSO), classical PI, and slide mode control (SMC). The BLDC motor–based BES algorithm showed better robustness, better accuracy for tracking reference speed, and better disturbance rejection than traditional controllers. The average rise time values of the SMC, PI, and PSO-PI techniques were 0.016 s, 0.048 s, and 0.023 s, respectively. In addition, the settling times were 0.61 s for the SMC method, 0.21 s for the PI method, and 0.012 s for the PSO-PI method. Finally, the BES–PI control was the best controller for BLDC motors, with average rise time values of 0.01 s, a settling time of 0.05 s, and no overshoot.