Optimizing BLDC motor drive performance using particle swarm algorithm-tuned fuzzy logic controller

Abstract A brushless DC (BLDC) motor is synchronous with trapezoidal/square wave counter-electromotive force, which a typical example of highly coupled nonlinear systems. In industrial control, BLDC drive usually uses proportional–integral (PI) controller to control the speed, but it very difficult adjust scale factors. this study, we present particle swarm algorithm-tuned fuzzy logic-PI (PF-PI) applied speed system. The objective paper optimally tune PI parameters obtain best response. factors are optimized using optimized-PI (P-PI) and PF-PI controller. three performance indicators integral time absolute error (ITAE), square (ITSE) (ISE) used measure effectiveness optimization. results show that optimal torque ripple response curves obtained by ITAE as indicator. conclusions demonstrate proposed method provides superior dynamic for motor. Highlights terms research content, propose new driven system based on traditional system, applicability discussed. method, compare no-load start, variable sudden addition disturbance load start capabilities P-PI controller, verify fast robustness significance, structure improved enhanced.