Traditional external slot-type fertilizer distributors exhibit significant pulsation during the fertilizing process, leading to poor uniformity of fertilizer application. To address these issues, a PID control method was proposed based on combination of segmented particle swarm optimization (PSO) and genetic algorithm (GA), and a corresponding precision fertilization control system was designed. This method leveraged the ability of PSO to quickly find local optimal solutions and the efficient global search capability of GA to achieve rapid response and high-precision fertilizer flow regulation in the precision fertilization system. The performance of the control algorithm was evaluated through fitness tests and segmented optimization tests, and a fertilization flow test platform was established for bench tests and soil bin tests to verify the adaptability of the controller in the field. The results showed that the GA PID algorithm optimized by PSO demonstrated significant advantages in the fitness test, converging to 0 in only 13 iterations, with higher precision and faster iteration speed compared with GA and PSO algorithms alone. The segmented optimization test indicated that the shortest response time of the precision fertilization control system was 0.36 s, which was 91.44% reduction compared with the system without the PSO-optimized GA algorithm. The average fertilization accuracy in bench tests and soil bin tests was 98.07% and 97.69%, respectively. These results demonstrated that the control algorithm met the requirements of rapid response and high-precision fertilization, enhanced the robustness of the control system, and provided theoretical and practical support for high-precision regulation of solid granular fertilizers.