The Application And Optimization Of The Fuzzy Control Theory In The Activated Sludge System

The activated sludge process is the most generally applied biological wastewatertreatment method. In the activated sludge process, a bacterial biomass suspension (theactivated sludge) is responsible for the removal of pollutants. Depending on the designand the specific application, an activated sludge wastewater treatment plant (WWTP) canachieve biological nitrogen (N) removal and biological phosphorus (P) removal, besidesremoval of organic carbon substances. Evidently, many different activated sludge processconfigurations have evolved during the years. A review on the historical evolution of theactivated sludge process can be found in.Because the process is the complex mechanism and it is highly nonlinear, strongcoupling, uncertainty, and include sewage into the water component of fluctuations in thegreat and other features, so it provides the set of effective simulation, modeling andcontrol strategies to improve the level of process automation and the treatment effect ofChina’s sewage treatment. It has great practical significance in alleviating the problem ofwater resources in China.The paper takes the process of the DO （dissolved oxygen） which is morerepresentative as the control object of activated sludge systems. It applies the fuzzycontrol theory to optimize this process, and it is compared with the ordinary PID control.In order to avoid the coupling interaction between the three output variables in the fuzzycontroller, the paper divides the commonly used two-inputs and three-outputs of themulti-dimensional fuzzy control model into three two-input single-output two-dimensionalfuzzy control model. From the simulation results, we know that ordinary PID control errorand fuzzy PID control error are within the allowable range, the fuzzy PID control in theerror control is more accurate, but also for the following optimal fuzzy control to providea certain basis.Taking into account the fuzzy control may be local optimal situation; this paper proposes the fuzzy control scheme based on genetic algorithm, the scheme’s main idea isto use a genetic algorithm to optimize fuzzy control rules and membership functions.When select the fitness function, this paper applies the typical ITAE（Integrated Time andAbsolute Error）function. At the same time, in order to avoid the excessive overshoot, wetake the punishment function. Once found the overshoot, we put the overshoot as anoptimal index, so that ITAE function is further improved. From the simulation results, wecan see that fuzzy PID control is more superior in terms of response speed, overshoot andsettling time superior than the conventional PID control; what is more, fuzzy PID controlbased on genetic algorithm goes a step in this superiority.