Investigated in this thesis is the application of a genetic algorithm (GA) for searching optimal parameters of a PID controller for a DC brushless rotary motor position control system. The gains of the PID controller are searched simultaneously through adaptive genetic algorithm (GA) whose adaptively crossover and mutation rate can avoid falling into local optimum and speed up the convergence. As for the experiment part, we use the DC brushless rotary motor, power amplifier and TI DSP (TMS 320LF2407) controller supported by Intelligent Control Technology Co., Ltd. to verify and improve the feasibility of controller. The results show that, the optimal PID controller designed by GA can track position command rapid.