Data Processing of Municipal Wastewater Recycling Based on Genetic Algorithm

Abstract

In order to accurately process the data of urban sewage recycling, this paper designs an adaptive genetic algorithm, which integrates genetic algorithm, adaptive genetic algorithm and traditional PID respectively, and designs simulation experiments to compare their performance. The simulation results show that the self-adaptive PID control algorithm is superior to the genetic PID control algorithm in both control accuracy and dynamic characteristics. The PID controller with good optimization performance is applied to the control object of sewage treatment system. Through simulation analysis, the adaptive genetic algorithm only needs 52s when adjusting the step response simulation. The overshoot of the system is 8%. The interference in the simulation is restored to a stable state within the interference 18S, and the adjustment time in the robustness simulation is reduced by about 15s compared with the genetic algorithm. In conclusion, the adjustment time of the system is shortened, the overshoot of the system is reduced, and the anti-interference and robustness are enhanced. For the dissolved oxygen concentration of the key object in the control system, the above controller with good performance is applied to the sewage treatment control system, which not only reduces the overshoot and regulation time, but also improves the control accuracy, and can well meet the control requirements of sewage treatment.