A DSP Based Dual-module Control System And Reduction Of Ripple Torque Of BLDCM

Because of its eminent performance, the brushless DC motor (BLDCM) has been broadly applied. The traditional theoretical analysis and designing method have been developed maturely. It can be said that the wider applications of BLDCM depend somewhat upon the further research on its special control method. In this paper, fuzzy control and neural network are adopted. When the gap between reference rotary speed and the feedback is huge, regulator based on the rule of fuzzy control is used, which can make the speed follow instruction very quickly. But this method can't kill tiny discrepancy. So when the gap is small enough, control strategy will switch to the method based on BP neural network. Since a fuzzy BP neural network dual-mode control mode is applied in this paper, the BLDCM control system which is a non-linear and strong coupled system, can gain features of self-adaptive, insensitive and robust to the change of parameters. Generation of BLDCM's ripple torque is analyzed in detail. Combined with the characteristic of DSP's symbol flags, the most suitable way is chosen to diminish the dead region of inverter bridge. Mathematic model of torque is induced. When phase current is switched, keeping the IGBT closed in the circuit can restrain the current delay caused by stator winding's inductance effect. Using TMS320lf2407 as control unit, program modules of fuzzy BP neural network dual-mode control method, output of PWM, feedback collection and A/D conversion are stored in the E2PROM. Verified by experiments, the all-digital control system based on DSP increases the real-time performance and realizes accurately speed control.