基于ESN的污水处理过程优化控制  

Optimal control for wastewater treatment process based on ESN neural network

作　　者：乔俊飞[1] 王莉莉[1] 韩红桂[1] 

机构地区：[1]北京工业大学电子信息与控制工程学院,北京100124

出　　处：《智能系统学报》2015年第6期831-837,共7页CAAI Transactions on Intelligent Systems

基　　金：国家自然科学基金重点基金资助项目(61533002);国家自然科学基金杰出青年基金资助项目(61225016);中国博士后科学基金一等资助项目(2014M550017);北京市教育委员会科研计划资助项目(KZ201410005002;km201410005001);高等学校博士学科点专项科研基金资助项目(20131103110016)

摘　　要：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。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.

关 键 词：污水处理过程 优化控制 状态回声网络 性能指标预测模型 基准仿真模型 

分 类 号：X703[环境科学与工程—环境工程]