污水处理决策优化控制

以抑制出水氨氮浓度、总氮浓度峰值和降低能耗为目标，提出污水处理决策优化控制方法.首先利用神经网络建立出水氨氮和总氮预测模型；其次使用多目标进化算法得到溶解氧浓度和硝态氮浓度设定值；最后，根据出水氨氮和总氮浓度预测结果选择控制策略（优化控制和抑制控制）.以仿真基准模型（BSM1）为平台，采用提出的决策优化控制方法进行控制，实验结果表明，该控制方法有效抑制了出水氨氮和总氮浓度峰值，出水超标时间和能耗明显少于所对比决策控制方法.

Advanced Decision and Optimization Control for Wastewater Treatment Plants

In order to inhibit the peak of ammonia nitrogen (S_{NH, e}) and total nitrogen (S_{Ntot, e}) concentrations in effluent and reduce energy consumption, we present in this paper a decision and optimization control method. Firstly, we establish the prediction models of S_{NH, e} and S_{Ntot, e} with neural network. Secondly, we optimize the set points of dissolved oxygen concentration and nitrate nitrogen concentration with multiobjective evolutionary algorithm. Lastly, select control strategy (optimal control strategy or inhibitory control strategy) based on the outcome of prediction models. Evaluation is carried out with the Benchmark Simulation Model No.1. The results show that the proposed method restrains the peaks of S_{NH, e} and S_{Ntot, e} effectively while the percentages of time of S_{NH, e} and S_{Ntot, e} violations are less than those of the compared inhibitory control methods, and that the energy consumption using the proposed method is less than that using the counterpart inhibitory control method significantly.