In view of the problems of large lag and nonlinearity in aeration control systems for wastewater treatment. The principles of aeration control systems were analyzed, meanwhile, mathematical model for such systems was established. Based on traditional PID(proportion, integration, differential) control algorithms, particle swarm optimization algorithms, and fuzzy control algorithms, an improved particle swarm optimized fuzzy PID algorithm was proposed to overcome the drawbacks of expert-dependency and lack of dynamic performance in fuzzy PID control. The system was simulated using MATLAB to compare the speed, accuracy, and stability of the three control methods in terms of step response, disturbance rejection, and robustness under model mismatch conditions. The results indicate that the improved particle swarm optimized fuzzy PID algorithm outperforms traditional PID and fuzzy PID control algorithms in terms of step response, disturbance rejection, and robustness. It achieves faster and more stable regulation of dissolved oxygen, thereby enhancing control system performance. The improvement is expected to reduce operational costs at wastewater treatment plants, as well as improve system reliability and economic efficiency.