CONTROL OF RECYCLE SLUDGE IN ACTIVATED SLUDGE PROCESS USING ADAPTIVE NEURO-FUZZY LOGIC CONTROLLER (ANFIS)

摘要

Activated sludge process is usually difficult to operate and control because of its complex operational behavior and of its complex nature. The optimization and further process development of this technology go the availability of fuzzy logic model, this model is powerful because it can learn to represent complicated data patterns or data relationships between input and output variables of the system being studied.The objective of this study is to determine the amount of sludge necessary to be recycled in the aeration tanks to allow the attainment of a good quality of effluent wastewater and to minimise the excess sludge, a fuzzy control model of activated sludge process was developed. The detailed information on development of fuzzy model was addressed based on collecting and analyzing previous experimental data.Neuro-fuzzy modeling should be able to determine the amount of recycle sludge necessary to treat an activated sludge treatment plant. The input parameters used in this study include the removal yields of organic pollution parameters such as COD and BOD, SS and recycle sludge as a decision parameter with respect to the discharge standards.The historical values of the observed yields associated with the recycle sludge during the study learning period enable the prediction of the recycle sludge needed for a validation period. Satisfactory results were obtained during the study and validation periods, revealing the advantages of fuzzy logic and justifying the predictive power of the model.