Optimized Angular Position Control of Brushless DC Motor Using Imperialist Competitive Algorithm Based on FOC and Trapezoidal Control

In this study, the Imperialist Competitive Algorithm (ICA) is used to optimize the gains of the cascaded position controller. Brushless DC (BLDC) motor drives with FOC and trapezoidal control structure are implemented in Simulink environment to provide an evaluation function of ICA. In this paper, a brief discussion has been conducted regarding the selection of settings and coefficients of ICA. Simulation results show that the optimized speed and position controller tracks the target speed and target position appropriately. Also, the effectiveness of ICA is verified by performance comparison of ICA, PSO, and GA in this paper.