Equilibrium Optimizer Based FOPID Control of BLDC Motor

The main challenges of proportional integral derivative (PID) control are sudden set-point changes and parameter changes, which leads to poor response. It can be taken into account that this unit replaced by another similar unit, but it differs from in the degree integration differentiation, is what known as fractional-order PID (FOPID), improves performance system transient state. To choose FOPID constants, various methodologies, including optimization algorithms, used obtain best possible performance. In paper, speed brushless DC motor (BLDC) was regulated using where equilibrium optimizer (EO) algorithm find values controller compared with several other algorithms such particle swarm (PSO), differential evolution (DE), golden jackal (GJO). Simulation results Matlab-Simulink 2016a showed effectiveness proposed achieving response time, overshot, lower steady state error rest algorithms.