Fuzzy Control and Optimization for the Wastewater Treatment Process

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There are increasingly important financial incentives and environmental consideration to improve the effluent quality of wastewater from domestic and industrial users. The activated sludge process is a widely used biological wastewater treatment process. The activated sludge process is complicated due to the many factors such as the variation of influent flowrate and concentration, the complexity of biological reactions and the various operation conditions. Nowadays, not only suspended solids and residual carbon, but also nitrogen and phosphorous concentration of the effluent water must be taken into account for the design and operation of wastewater treatment plants. Also, the effluent quality to be met are more stringent. Therefore, an intelligent control approach is required in order to successful biological nitrogen removal. In this paper, the strategies for dosage of extra carbon in the anoxic zone and DO concentration in the aerobic zone are presented and evaluated through the simulation using the denitrification layout of the IWA simulation benchmark implemented by Matlab$\^$/5.3/Simulink$\^$/3.0. The control strategy to achieve sufficient denitrification rates in an anoxic zone. Methanol is used as an external extra carbon source. The external extra carbon source is required for the nitrogen removal process because nitrogen and organic concentration are fluctuated in the influent flowrate. The dissolved oxygen is calculated by So concentration in the activated sludge model NO.1. The air flowrate of each aerobic reactor is intelligently controlled to achieve the predefined setpoints. Air flowrate is adjusted by the fuzzy logic controller that includes two inputs and one output. The objective function for the optimization procedure is designed to improve effluent quality and reduce the operating cost.