Abstract
A double-loop control system based on human-simulated intelligent control (HSIC) is designed using a mathematical model of a brushless DC motor (BLDCM). In the double-loop motor control system, a conventional PI controller is implemented for the current loop and an HSIC speed controller using the characteristic model-based multi-mode control is adopted for the speed loop. The controller parameters are set and optimized using an improved genetic algorithm (IGA). Compared with the double-loop motor subject to adaptive PID control, fuzzy control, neural-network control and conventional PID control, simulation results show the double-loop motor control system of the HSIC-based BLDCM has high dynamic and static performances as well as high adaptability and robustness.
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