基于模糊神经网络的污水处理生化除磷过程控制

FNN-based process control for biochemical phosphorus in WWTP

针对污水处理生化除磷过程中出水总磷难以实时达标的问题,提出了一种基于模糊神经网络(fuzzy neural network,FNN)的出水总磷控制方法。首先,通过分析污水处理生化除磷机理,确定了控制器的操作变量为生化反应池第五分区外部碳源(external carbon, EC)与溶解氧(dissolved oxygen, DO)传递系数。其次,设计了一种基于FNN的出水总磷控制器,采用梯度下降算法更新控制器参数;最后,将基于FNN的出水总磷控制器应用于污水处理过程基准仿真平台(benchmark simulation model No.1,BSM1),实验结果表明,基于FNN的出水总磷控制器能够保证出水总磷的达标排放,具有较好的控制效果。

To make the effluent total phosphorus reach the real-time standard in wastewater treatment process(WWTP), an effluent total phosphorus control strategy, based on fuzzy neural network(FNN), is proposed to control the biochemical phosphorus in this paper. First, the manipulated variables, based on the mechanism analysis of biochemical phosphorus removal process, were considered as the external carbon(EC) and dissolved oxygen(DO)transfer coefficient. Second, an FNN-based process controller was designed to control the effluent total phosphorus.And a gradient descent algorithm was applied to adjust the parameters of controller. Finally, the proposed FNNbased process controller was tested on the benchmark simulation model No. 1(BSM1) to evaluate its effectiveness.The results demonstrated that the proposed FNN-based process controller can guarantee the standard discharge of effluent total phosphorus. The results show that the FNN-based effluent total phosphorus controller can ensure that the total effluent total phosphorus is discharged and has a good control effect.