The Intelligent Control Of Wastewater Treatment Process Based On Fuzzy Neural Network

Activated sludge process is a kind of effective method, which consumes the pollutant in wastewater by microorganisms'metabolism. Due to the violent change of influent and the complexity of microorganisms'growth, the activated sludge processes have characteristics of muti-variables, strong coupling, high non-linearity, big lag and indetermination, which result in laggard automation of wastewater treatment process. To ensure that the treatment process run well and enhance effluent quality, it has become an important task in the field of wastewater treatment to research new control method. Researching the intelligent control strategy in wastewater treatment can not only enrich theory and application of intelligent control, but also is useful to the development of control theory, which can provide new control way for nonlinear and complicated systems.In the paper, on the basis of thorough analyzing past achievements, the author studied intelligent control technology of activated sludge wastewater treatment process. The main content of this paper is as follows:(1) Summarized the automatic control strategies in wastewater treatment.(2) Analyzed the inherent mechanism of activated sludge, established mathematics model, which reflects the relations among dissolved oxygen, microorganism and substrate.(3) Aiming at the complexity of activated sludge system, and combining the hotspot of intelligent control, we designed fuzzy neural network controllers, expatiated their structures and optimization algorithms, and respectively applied them to the control of dissolved oxygen concentration and sludge age.â‘ Designed four layers fuzzy neural network to control the dissloved oxygen concentration in the sequencing batch reator and the complex mix bioreactor with continuous influent. The result of simulation experiments confirms the feasibility of control strategy and proves the robustness and self-adaptability of fuzzy neural network controller.â‘¡Designed five layers fuzzy neural network to control the sludge age in the complex mix bioreactor. The results of experiments indicated that the controller can keep the actived sluge concentration in reactor at a proper level and make sludge have good decontamination ability and settle capability.