Speed and Displacement Control System of Bearingless Brushless DC Motor Based on Improved Bacterial Foraging Algorithm
To solve the deficiencies of long optimization time and poor precision existing in conventional bacterial foraging algorithm (BFA) in the process of parameter optimization, an improved bacterial foraging algorithm (IBFA) is proposed and applied to speed and displacement control system of bearingless brushless DC (Bearingless BLDC) motors. To begin with the fundamental principle of BFA, the proposed method is introduced and the individual intelligence is efficiently used in the process of parameter optimization, and then the working principle of bearingless BLDC motors is expounded. Finally, modeling and simulation of the speed and displacement control system of bearingless BLDC motors based on the IBFA are carried out by taking the software of MATLAB/Simulink as a platform. Simulation results show that, speed overshoot, torque ripple and rotor position oscillation are dramatically reduced, thus the proposed method has good application prospects in the field of bearingless motors.