عنوان مقاله :
A Neural Network-PSO Based Control for Brushless DC Motors for Minimizing Commutation Torque Ripple
عنوان به زبان ديگر :
A Neural Network-PSO Based Control for Brushless DC Motors for Minimizing Commutation Torque Ripple
پديد آورندگان :
Aghashabani، M نويسنده BSc, Department of Science, Payame-Noor University, Boroojen Branch Aghashabani, M , Milimonfared، J نويسنده Professor, Department of Electrical Engineering, Amirkabir University of Technology Milimonfared, J , Kashefi Kaviani، A نويسنده MSc, Department of Electrical Engineering, Florida International University Kashefi Kaviani, A , Ashabani، M نويسنده MSc, Department of Electrical and Computer Engineering, University of Alberta Ashabani, M
اطلاعات موجودي :
دوفصلنامه سال 1389 شماره 15
كليدواژه :
BLDC machines , Commutation , Optimized input voltage , Torque ripple
چكيده لاتين :
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 doesnʹt 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.
عنوان نشريه :
مجله انجمن مهندسين برق و الكترونيك ايران
عنوان نشريه :
مجله انجمن مهندسين برق و الكترونيك ايران
اطلاعات موجودي :
دوفصلنامه با شماره پیاپی 15 سال 1389
كلمات كليدي :
#تست#آزمون###امتحان
