Goz, EdaYuceer, Mehmet2024-08-042024-08-0420181018-46191610-2304https://hdl.handle.net/11616/103233Activated sludge process has a complex and nonlinear characteristics, therefore, various conventional control algorithms are incapable of controlling activated sludge process. On the other hand, optimizations of waste water treatment plants have been inevitable due to the strict regulations. This paper deals with the application of fractional order proportional integral and derivative controller ((PID mu)-D-lambda), fractional order proportional integral (PI lambda) and classical PID and PI controller for activated sludge waste water treatment plants. For this purpose, a simpler model with single aeration bioreactor that includes biological process with one type of substrate and microorganism was used. Since the level of dissolved oxygen in the aeration tank is important for the effluent quality standards and minimizing the operating cost, it was chosen as the controlled variable. Moreover, manipulated variable has been defined as aeration rate. Performances of PID, PI, fractional order PID and fractional order PI controller were evaluated with integral square error (ISE). The simulation results indicated that fractional order PID controller exhibited a better performance than fractional order PI, conventional PID and PI controllers. Controller parameters were calculated via various optimization strategies such as particle swarm optimization (PSO), genetic algorithm (GA) and sequential quadratic programming (SQP). The values of fractional order PID and PI controller parameters were almost the same even if different optimization methods were tried for determining the controller parameters. Fractional order PID and fractional order PI controller parameters were obtained as K-p = 29.8916, K-I = 29.913, K-D = 29.8909, lambda = 1.0934, mu = 0.01612 and K-p = 29.9999, K-I = 29.9999, lambda = 0.995, respectively. Similarly, conventional PID parameters were not affected by different optimization methods. Both GA and PSO show the same controller parameters (K-p = 29.9997, tau(I) = 29.9998, tau(D) = 29.9993). Furthermore, conventional PID parameters that are manipulated by Ziegler Nichols method were K-p = 46, tau(I) = 115, tau(D) = 4.6.eninfo:eu-repo/semantics/closedAccessActivated Sludge ProcessFractional order controllerParameter estimationArticle271280718080WOS:000455562400019Q4