基于多目标粒子群算法的污水处理过程优化控制策略  

Optimal Control Strategy of Sewage Treatment Process Based on Multi-objective Particle Swarm Optimization

作　　者：邓鑫 宁芊[1] Deng Xin;Ning Qian(College of Electronics and Information,Sichuan University,Chengdu,China)

机构地区：[1]四川大学电子信息学院,四川成都

出　　处：《科学技术创新》2025年第11期74-77,共4页Scientific and Technological Innovation

摘　　要：污水处理过程的运行条件可能会发生动态变化,因此需要根据不同操作条件采取适当的措施以优化关键性能指标。本文提出了一种动态优化控制策略。首先,采用径向基神经网络建立水质和能耗模型。然后,利用动态多目标粒子群优化算法求解最优设定值。最后,通过基准仿真模型验证了所提出策略的有效性。实验结果表明,该策略不仅能够显著优化能耗和出水水质,还提升了控制系统的动态适应性。Operating conditions in wastewater treatment processes can change dynamically,so appropriate measures need to be taken to optimize key performance indicators based on different operating conditions.In this paper,a dynamic optimization control strategy is proposed.Firstly,the radial basis neural network was used to establish the water quality and energy consumption model.Then,the dynamic multi-objective particle swarm optimization algorithm was used to solve the optimal setpoint.Finally,the effectiveness of the proposed strategy is verified by the benchmark simulation model.Experimental results show that the proposed strategy can not only significantly optimize the energy consumption and effluent quality,but also improve the dynamic adaptability of the control system.

关 键 词：污水处理 多目标优化 跟踪控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]