面向污水处理溶解氧浓度的智能优化控制  

Intelligent Optimization Control of Dissolved Oxygen Concentration for Wastewater Treatment

作　　者：崔心惠 李文萱[1] 詹玉新 Cui Xinhui;Li Wenxuan;Zhan Yuxin(Chuzhou Polytechnic,Chuzhou239000,China)

机构地区：[1]滁州职业技术学院,安徽滁州239000

出　　处：《滁州职业技术学院学报》2021年第3期57-62,共6页Journal of Chuzhou Polytechnic

基　　金：安徽省高校优秀青年人才支持计划重点项目(gxyqZD2020068);智能移动式污水处理远程监控系统研究(YJY-2020-25)。

摘　　要：针对污水处理过程中溶解氧时变、非线性而无法实现跟踪控制问题,根据进水水质不同,建立自适应粒子群算法优化RBF神经网络参数的预测模型,将实时预测参数作为溶解氧动态寻优模型的闭环反馈输入信号,然后动态优化溶解氧浓度设定值并以PID控制器进行跟踪以达到动态调整溶解氧浓度的智能控制效果。仿真结果表明,该方法在实现出水氨氮的高预测精度基础上,可以对溶解氧变化进行快速准确优化控制,具有良好的动态性能。To solve the time-varying and nonlinear problem ofDO inwastewater treatment process,a prediction model of RBF neural network parameters optimized by adaptive particle swarm optimization algorithm is established according to different influent water quality.The real-time prediction parameters are used as the closed-loop feedback input signal of DO dynamic optimization model,and DO concentration setting value is dynamically optimized.Finally,PID controller is used to achieve the intelligent control of dynamic adjustment of dissolved oxygen concentration.The simulation results show that the method can optimize the dissolved oxygen quickly and accurately with good dynamic performance.

关 键 词：RBF神经网络 溶解氧浓度 自适应PID 智能优化 

分 类 号：TP23[自动化与计算机技术—检测技术与自动化装置]