Research On Optimization Control For Wastewater Treatment Process Based On Improved Multi-Objective Cuckoo Search Algorithm

The shortage of water resources and massive water pollution events have made the wastewater treatment an important position around people.It is an effective way to establish wastewater treatment plants to purify water and protect the environment.The wastewater treatment process(WWTP)has the characteristics of high nonlinearity,large time variation,large lag and strong coupling,which makes it difficult to control.However,the traditional control method has the problems of poor effluent quality,high energy consumption and operation cost during the wastewater treatment process.Therefore,studying new and effective optimization control schemes of wastewater treatment process is an important measure to alleviate the deterioration of ecological environment and achieve energy conservation,and sustainable development.The activated sludge method wastewater treatment benchmark simulation model No.1(BSM1)is used as the simulation object based on the problems existing in the WWTP in this thesis.Combined with the characteristics of WWTP and neural network characteristics,the optimization and control methods based on improved multi-objective cuckoo search algorithm(IMOCS)are proposed to realize optimal control of wastewater treatment process.The main research contents of the thesis are as follows:1.The BSM1 model is established on the MATLAB platform.Then,the established model is used as the simulation object.The wastewater data file provided by European co-operation in the field of scientific and technical research(COST)is used to simulate the dynamic changes of pollutant concentration and influent flow under different weather conditions,which lays a foundation for the follow-up study of the control strategy of biological wastewater treatment system.2.Aiming at how to determine the set values of dissolved oxygen and nitrate nitrogen controllers in wastewater treatment process,an optimized control method for wastewater treatment based on IMOCS is proposed.Firstly,the back propagation neural network-based wastewater treatment model is established by analyzing the wastewater treatment process;Then,considering the characteristics of large time-varying and strong coupling in WWTP,the convergence of multi-objective cuckoo search algorithm(MOCS)is improved based on Pareto distribution and dynamic step size to optimize the objective function and determine the optimized set values of dissolved oxygen and nitrate nitrogen.Finally,the proportion integration differentiation(PID)controller is used to track and control the optimized set values of key variables to achieve multi-objective optimization control of WWTP.The simulation results based on BSM1 reveal that compared with other methods,the proposed method can better reduce the energy consumption of wastewater treatment process while ensuring that the effluent water quality parameters meet t he standard.3.The keys of wastewater treatment process optimization control research is th e modeling between control variables and objective functions,the decoupling between objective functions and the tracking control of the bottom loop.It is not poss ible to maximize energy conservation and protect the environment by simply studying a certain part.Based on this,an intelligent optimization control method for wastewater treatment process based on hybrid multi-object cuckoo search algorithm(HMOCS)is proposed.Firstly,the Takagi-Sugeno fuzzy neural network(TSFNN)wastewater treatment model is established due to the nonlinear and strong coupling characteristics of the wastewater treatment process;Then,in view of the coupling and dynamic characteristics of wastewater treatment process,a hybrid multi-object cuckoo algorithm is used for optimization based on dynamic step size,discovery probability combined with the optimization ability of non-dominated sorting genetic algorithm-II(NSGA-II)to improve the diversity and convergence of the algorithm.The obtained hybrid multi-objective cuckoo search algorithm is used to find the dynamic optimal set value of the controller;Finally,a fuzzy controller is used for tracking control of the underlying loop of the wastewater treatment.The simulation results based on BSM1 reveal that the proposed method can be effectively applied in the wastewater treatment process to achieve energy conservation and protect the environment.