An Improved Tuning of PID Controller for PV Battery-Powered Brushless DC Motor Speed Regulation Using Hybrid Horse Herd Particle Swarm Optimization

In this study, speed control of PV battery-powered brushless DC motor (BLDC) is controlled by novel hybrid horse herd particle swarm optimization- (HHHPSO-) tuned proportional integral derivative (PID) controller. The optimal gain parameter the PID controller optimization algorithm. purpose newly developed HHHPSO algorithm to enhance performance classic (HHA), specifically in two different ways. first place, it bolsters HHA’s aptitude for exploratory learning related ageing issue. By doing so, possible circumvent phenomenon local minimum stagnation. Second, permits HHA have a superior capability exploitation with assistance hybridization through utilisation optimization. This technique helps improve rate convergences method. time domain-based indices were considered as an objective function such addition squared error, current and electromagnetic torque error finding values using HHHPSO. proposed HHHPSO-tuned BLDC tested various working conditions constant conditions, varying load also compared state-of-the-art method has quick rise around 20-21 msec, settling 35-39 zero steady-state overshoot than techniques hardware confirm suitability real-time applications.