基于ESN的污水处理过程优化控制

针对污水处理过程能耗过高的问题,提出了一种基于状态回声网络(ESN)的在线优化控制方法。建立了污水处理过程预测模型,实现性能指标的预测;根据系统的状态以及预测的性能指标,采用ESN实时优化控制变量的设定值;将优化后的设定值传送给底层控制器进行跟踪控制。将ESN优化控制方法在污水处理过程基准仿真模型(BSM1)上进行了验证,实验结果表明,该方法不但能够满足出水水质的要求,而且降低了污水处理过程运行成本。

Optimal control for wastewater treatment process based on ESN neural network

To address the problem of the high-energy consumption in wastewater treatment processes, we propose an online optimal control method based on an echo state network(ESN). This method has three main steps. First, we develop a performance prediction model of the wastewater treatment process. Second, based on the system state and the predicted performance index, we optimize the set point of the control variable using the ESN in real time. Then we transfer the optimized set point to the underlying controller for tracking control. This ESN-based online optimal control method is carried out using the benchmark simulation model 1(BSM1). The simulation results show that the proposed method can not only meet the effluent quality requirements, but also efficiently reduce the operation costs of the wastewater treatment process.