Research On Optimization Control Of Wastewater Treatment Process Based On MOEA/D

With the acceleration of urbanization and industrialization in China,the discharge of urban sewage is also increasing.However,the sewage treatment process has problems of high energy consumption and high operating cost.Therefore,meeting the discharge standards for wastewater treatment with minimum energy consumption costs and achieving precise control requirements are important issues in the current intelligent urban construction.In this study,the accurate prediction model of effluent water quality and the sewage treatment process to meet the emission standards with the lowest energy consumption limit are taken as the research objectives,and the intelligent optimization control method is combined in the sewage treatment process.In this study,aiming at the difficulty in establishing predictive model and low control precision in wastewater treatment process,combined with the characteristics of nonlinearity,large time lag and strong coupling in wastewater treatment process,an intelligent optimization method for wastewater treatment process based on decomposition-based multi-objective evolutionary algorithm is designed.Combined with the fuzzy neural network control method,the optimal control of the dissolved oxygen concentration and the nitrate nitrogen concentration in the sewage treatment process is improved,and the energy consumption and the operating cost of the sewage treatment plant are reduced under the condition that the effluent water quality meets the standard.At the same time,the development of the sewage treatment intelligent system was completed,and the sewage environment was effectively monitored through the intelligent control platform.The research work in this study is mainly divided into the following points:(1)In view of the difficulty of establishing prediction model in the process of sewage effluent quality detection,this paper takes COD as an example,establishes RBF neural network residual feedback on the basis of Grey Model(GM),which provides prediction compensator for grey prediction model and solves the low precision problem of grey model prediction,so as to realize the key water in the process of sewage treatment.The high precision prediction of COD is the basis for the modeling process of wastewater treatment optimization objectives.(2)Sewage energy consumption and water quality optimization method based on improved MOEA/D algorithm.In this paper,two contradictory evaluation indexes of effluent quality and energy consumption in wastewater treatment process are improved on the decomposition-based multi-objective evolutionary algorithm(MOEA/D),and the second optimization is performed on the basis of the improvement.The algorithm makes the solution found in the multi-objective problem of persuasion energy and effluent water quality as uniform as possible,and obtains the optimal set value of dissolved oxygen and nitrate nitrogen concentration,which solves the complicated variables in the optimization control process and is difficult to realize real-time.Optimization problem.(3)Research on tracking control of wastewater treatment based on G-SOFNN.In order to ensure that the controller can achieve the set value with high precision in the intelligent optimization control method,this paper improves the SOFNN controller and improves the adjustment of the self-organizing fuzzy neural network controller in the process of structural adjustment through the idea of genetic variation.Efficiency,and through the projection algorithm to learn the parameters of the controller network,to avoid falling into local optimum,thereby improving the intelligent controller’s control accuracy of dissolved oxygen concentration.(4)Sewage treatment monitoring system design.The sewage treatment system mainly combines configuration software,database and MATLAB software.The main system functions include: sewage treatment process control interface,communication between configuration and database,and call of sewage treatment control program.In the design process of the control system,first,the interface of the system is designed by using the configuration software.Then,through the ODBC technology,the variables detected in the sewage environment are stored in the SQL Server 2008 database,and the control program is written through MATLAB.Finally,through the mutual transmission of information between the user management module,database,control program and other modules,real-time monitoring of the sewage environment and control of dissolved oxygen concentration in the sewage to achieve intelligent control of the sewage environment,for future control methods The comparison provides an idea.