Ant Colony Algorithm Based Fuzzy Control for a Brushless DC Motor

The brushless DC motor (BLDCM) is a multi-variable and non-linear system. Fuzzy control has been widely used in the field of the BLDCM control. However, the design and tuning of the fuzzy controller are not satisfactory. In this paper, an auto-tuning method for fuzzy logic controller based on ant colony optimization (ACO) algorithm is presented, and the controller is applied to control the BLDCM. The operating system includes a current loop and a speed loop. The speed loop uses the fuzzy logic controller whose control rules are optimized off-line and parameters are adjusted on-line based on ACO. At last, a digital signal processor (DSP) is used to fully prove the flexibility 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