SPEED CONTROL OF BRUSHLESS DC MOTOR USING GENETIC ALGORITHM BASED FUZZY CONTROLLER

The brushless DC motor (BLDCM) is receiving wide attention for industrial applications because of their high torque density, high efficiency and small size. Conventional controllers suffer from 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 which is given below. 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. 

BLDCM Servo System
Fig. I shows the block diagram of the configuration of fuzzy model control system for BLDCM. The inner loop of Fig. I limits the ultimate current and ensures the stability of the servo system. The outer loop is designed to improve the static and dynamic characteristics of the BLDCM servo system. In this paper, a fuzzy control is used to make the outer loop more stable. To make the fuzzy controller more robust, this paper presents the genetic algorithm to optimize the fuzzy rules, and auto-tuning the coefficient of the controller. 

Fig. II is the control configuration of the BLDCM servo system. The TMS320LF2407A DSP is used to generate the PWM and an IR2130 is used to drive the MOSFET. The A/D Unit is used to sample the current of the motor. The position signal of the rotor in gained by the Capture Unit of the DSP, and the speed value is calculated from the position information.

VIDEO DEMO