In order to solve the contradiction between the steady-state accuracy and overshoot in the application of the high-order control method in the photoelectric servo tracking systems, a fuzzy Ⅱ-order controller optimized by multiple population genetic algorithm (MPGA) was designed. In this method, an integrator was connected in parallel before the speed loop of the classic Ⅰ-type double closed-loop feedback controller to increase the system order to the Ⅱ, thereby speeding up the reaction speed and reducing the steady-state error. Therefore, a fuzzy logic controller (FLC) was introduced to dynamically adjust the gain of the integrator according to the state of the system to achieve dynamic high-order control, which not only suppresses system oscillation but also ensures steady-state accuracy. MPGA was used to optimize the input and output scale factors of FLC to obtain the optimal control parameters. The control system was analyzed theoretically, and the optimized system in each stage was compared with experiments. The results show that under the same experimental conditions, the MPGA-optimized fuzzy Ⅱ-order control system is used to realize the dynamic high-order control of the system, which can not only ensure that the overshoot of the original system remains the same, but also reduce the steady-state error by 88.55%. This study significantly improves the steady-state accuracy of the control system. The research is helpful to optimize the photoelectric servo tracking system.