Process Control And Optimization Of The City Wastewater Treatment

There are physical, chemical, and biological three traditional processingmethods in wastewater treatment. Biological wastewater treatment mechanismis the most complex, but this method is the most widely used. It is the mainway to deal with sewage and industrial wastewater. Since the1980, the fieldhas made great development. The biological method is the artificial simulationof natural water self-purification process, to provide adequate oxygen for thewastewater to shorten the time of water self-purification. The oxygen supplyunit is the core of the treatment, and the major energy-consuming unit.The thesis studied the biological wastewater treatment process, thereaction mechanism and the sewage treatment system modeling, control andoptimization, focuses on the control of dissolved oxygen concentration in thewastewater treatment process, and overall system optimization. Reference theconcentration of dissolved oxygen control methods and strategies combinedwith domestic wastewater treatment status, based on the air flow, dissolvedoxygen nonlinear PID control method is presented. Relative to otherintelligent control methods, easier to design and implementation, with greaterengineering significance. In our country， serious water shortages, water pollution, domesticwastewater treatment work is unsatisfactory. The wastewater treatment rate islow. The reason of the situation is largely inadequate investment and ashortage of funds. This also explains the high cost of wastewater treatment ofthis situation. The paper focuses on the overall optimization of biologicaltreatment units in wastewater treatment. Optimal control of dissolved oxygenconcentration and sludge emissions, and create response surface of the system.Different search methods are used for optimization and contrast. Thesimulation results show that the different starting points affect the optimizationresult. The first work before the optimization establishing the system responsesurface. In addition, the simulation results show that curve path optimization isfaster.