RT - Journal Article T1 - A Neural Network-PSO Based Control for Brushless DC Motorsfor Minimizing Commutation Torque Ripple JF - jiaeee YR - 2010 JO - jiaeee VO - 7 IS - 2 UR - http://jiaeee.com/article-1-210-fa.html SP - 15 EP - 22 K1 - BLDC machines K1 - Commutation K1 - Optimized input voltage K1 - Torque ripple AB - This paper presents the method of reducing torque ripple of brushless DC (BLDC) motor. The commutation torque ripple is reduced by control of the DC link voltage during the commutation time. The magnitude of voltage and commutation time is estimated by a neural network and optimized with an optimization method named particle swarm optimization (PSO) algorithm analysis. The goal of optimization is to minimize the error between the command torque and real torque and doesn’t need knowledge of the conduction interval of the three phases. It adaptively adjusts the DC link voltage in commutation duration so that commutation torque ripple is effectively reduced. In this paper, the performance of the proposed brushless DC (BLDC) control is compared with that of conventional BLDC drives without input voltage control. LA eng UL http://jiaeee.com/article-1-210-fa.html M3 ER -