针对污水处理曝气控制系统存在滞后大、非线性的问题，分析了污水处理曝气控制系统的原理，建立了污水处理曝气控制系统的数学模型；并通过对传统比例-积分-微分（proportion, integration, differential, PID）控制算法、粒子群算法和模糊控制算法的研究，提出了一种改进的粒子群优化模糊PID算法，有效解决了模糊PID控制过度依赖专家经验、缺少动态性能的缺点。采用MATLAB对该系统进行仿真，从阶跃响应、抗干扰性和模型失配情况下的鲁棒性三个方面，对三种不同控制方法的快速性、准确性和稳定性进行比较。结果表明，基于改进的粒子群模糊PID算法在阶跃响应、抗干扰能力和鲁棒性方面均优于传统PID和模糊PID控制算法，能够更快速、更稳定地实现对溶解氧的高效调节，改善了控制系统性能，有助于降低污水处理厂的运营成本。

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.