title: Improving the efficiency of dissolved oxygen control using an on-line control system based on a genetic algorithm evolving FWNN software sensor.
abstract: This work proposes an on-line hybrid intelligent control system based on a genetic algorithm (GA) evolving fuzzy wavelet neural network software sensor to control dissolved oxygen (DO) in an anaerobic/anoxic/oxic process for treating papermaking wastewater. With the self-learning and memory abilities of neural network, handling the uncertainty capacity of fuzzy logic, analyzing local detail superiority of wavelet transform and global search of GA, this proposed control system can extract the dynamic behavior and complex interrelationships between various operation variables. The results indicate that the reasonable forecasting and control performances were achieved with optimal DO, and the effluent quality was stable at and below the desired values in real time. Our proposed hybrid approach proved to be a robust and effective DO control tool, attaining not only adequate effluent quality but also minimizing the demand for energy, and is easily integrated into a global monitoring system for purposes of cost management.
authors.affiliation: School of Environmental Science and Engineering, Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, Sun Yat-Sen University, Guangzhou 510275, PR China.
authors.forename: Jujun
authors.initials: J
authors.lastname: Ruan
authors.affiliation: Department of Water Resources and Environment, Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou 510275, PR China.
authors.forename: Chao
authors.initials: C
authors.lastname: Zhang
authors.affiliation: Department of Water Resources and Environment, Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou 510275, PR China.
authors.forename: Ya
authors.initials: Y
authors.lastname: Li
authors.affiliation: Department of Water Resources and Environment, Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou 510275, PR China.
authors.forename: Peiyi
authors.initials: P
authors.lastname: Li
authors.affiliation: Department of Water Resources and Environment, Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou 510275, PR China.
authors.forename: Zaizhi
authors.initials: Z
authors.lastname: Yang
authors.affiliation: Department of Water Resources and Environment, Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou 510275, PR China.
authors.forename: Xiaohong
authors.initials: X
authors.lastname: Chen
authors.affiliation: Department of Water Resources and Environment, Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou 510275, PR China. Electronic address: huangmzh6@mail.sysu.edu.cn.
authors.forename: Mingzhi
authors.initials: M
authors.lastname: Huang
authors.affiliation: School of Environmental Science and Engineering, Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, Sun Yat-Sen University, Guangzhou 510275, PR China. Electronic address: zhangt47@mail.sysu.edu.cn.
authors.forename: Tao
authors.initials: T
authors.lastname: Zhang
mesh_terms: D019149:Bioreactors; D017143:Fuzzy Logic; D006801:Humans; D007220:Industrial Waste; D016571:Neural Networks, Computer; D009862:Online Systems; D010100:Oxygen / Q000737:chemistry*; D012984:Software; D012996:Solutions; D062065:Wastewater
chemical_list: D007220:Industrial Waste; D010100:Oxygen; D012996:Solutions; D062065:Wastewater
keywords: Dissolved oxygen control; Genetic algorithm evolving fuzzy wavelet neural network; Software sensor; Wastewater treatment process