化工学报2017，Vol.68Issue(4)：1516-1524,9.DOI:10.11949/j.issn.0438-1157.20161514
基于自组织模糊神经网络的污水处理过程溶解氧控制
Dissolved oxygen control of wastewater treatment process using self-organizing fuzzy neural network
摘要
Abstract
A self-organizing fuzzy neural network (SOFNN) control method is proposed, and its application system is designed for controlling the dissolved oxygen (DO) concentration in the activated sludge wastewater treatment processes. The neurons of rule layer are grown or pruned adaptively based on firing strength and mutual information to meet dynamic change of the real operating condition. Meanwhile, the centers and widths of membership functions and weights of output layer are trained by gradient descent optimization algorithm to ensure the convergence of SOFNN. The stability of the control system is proved based on the analysis of the learning rates of parameters in SOFNN by applying the Lyapunov stability theory. This control strategy is investigated and evaluated based on international Benchmark Simulation Model No.1 (BSM1). Experimental results demonstrate that the SOFNN controller performs better than PID, fuzzy logical control (FLC), model predictive control (MPC), and some other existing control methods. Performance comparisons indicate that the proposed SOFNN control strategy obtains higher tracking accuracy, better control placidity and superior adaptive capability.关键词
污水/溶解氧/过程控制/神经网络/自组织模糊神经网络/互信息Key words
wastewater/dissolved oxygen/process control/neural network/self-organizing fuzzy neural network/mutual information分类
信息技术与安全科学引用本文复制引用
周红标..基于自组织模糊神经网络的污水处理过程溶解氧控制[J].化工学报,2017,68(4):1516-1524,9.基金项目
淮安市科技支撑计划项目(HAG2014001). supported by the Huai'an Foundation for Development of Science and Technology (HAG2014001). （HAG2014001）
