Speed control of brushless DC motor using genetic algorithm based fuzzy controller
Changliang Xia, PeiJian Guo, Tingna Shi, M. H. WANG · 2005
. Abstract - The brushless DC motor (BIBCM) is receiving wide attention for industrial applications because of their high torque density, high efficiency and small size. Conventional eontrollers suffer hm uncertain parameters and the non-linear of the BLDCM. The fuzzy control has been focus in the field of the control of the BLDCM. However, a systematic method for designing and tuning the fuzzy logic controller is not developed yet. In this paper, an auto-tuning method for fuzzy logic controller based on the genetic algorithm (GA) is presented. And the scheme is applied into the BLDCM control. Two closed loops are constructed in this paper. The inner loop is current feed back which is to adjust the torque of the motor. The outer loop is the fuzzy logic controller whose control rules are optimized off-line and parameters are adjusted based on the genetic algorithm. In this paper, a program is written in Visual C++ to adjust the fuzzy controller off-line. At last, a TMS320LF2407A digital signal processor (DSP) is used to fully prove the fle!uibility of the control scheme in real time. Excellent flexibility and adaptability as well as high precision and good robustness are obtained by the proposed strategy.