FRACTIONAL-ORDER CONTROL STRATEGIES FOR THE ACTIVATED SLUDGE PROCESS

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dc.authoridYuceer, Mehmet/0000-0002-2648-3931
dc.authoridGoz, Eda/0000-0002-3111-9042
dc.authorwosidYuceer, Mehmet/E-5110-2012
dc.authorwosidGoz, Eda/AAH-3388-2020
dc.contributor.authorGoz, Eda
dc.contributor.authorYuceer, Mehmet
dc.date.accessioned2024-08-04T20:58:52Z
dc.date.available2024-08-04T20:58:52Z
dc.date.issued2018
dc.departmentİnönü Üniversitesien_US
dc.description.abstractActivated 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.en_US
dc.identifier.endpage8080en_US
dc.identifier.issn1018-4619
dc.identifier.issn1610-2304
dc.identifier.issue12en_US
dc.identifier.startpage8071en_US
dc.identifier.urihttps://hdl.handle.net/11616/103233
dc.identifier.volume27en_US
dc.identifier.wosWOS:000455562400019en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherParlar Scientific Publications (P S P)en_US
dc.relation.ispartofFresenius Environmental Bulletinen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectActivated Sludge Processen_US
dc.subjectFractional order controlleren_US
dc.subjectParameter estimationen_US
dc.titleFRACTIONAL-ORDER CONTROL STRATEGIES FOR THE ACTIVATED SLUDGE PROCESSen_US
dc.typeArticleen_US

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