自适应神经元——模糊推理系统在污水曝气控制中的应用

Application of adaptive neuro-fuzzy inference system on aeration control of wastewater treatment

曝气控制是保证污水处理厂水质和降低能耗的重要环节。本文考虑污水处理厂出水水质和曝气量的非线性、大滞后、时变性等特点,利用反向传播(BackPropagation——BP)算法对隶属度函数进行优化,建立模糊推理规则,并设计了一个自适应神经元——模糊控制系统,该系统对某SBR小型污水处理厂曝气进行了仿真分析,结果表明设计的控制系统的有效性。

Considering the delay,time-varying and nonlinear characteristic of wastewater treatment system,an adaptive fuzzy control system is developed for Demand Aeration Tank-Intermittent Tank, whose precise mathematical model is difficut to be established.BP algorithm is applied to optimize the membership functions.The Simulink of Matlab is used to simulate the proposed model and reach several promising results.