Iterative-ADP-algorithm-based optimal control method for wastewater treatment

Abstract

The invention provides an iterative-ADP-algorithm-based optimal control method for wastewater treatment. With the method provided by the invention, a problem of controlling of dissolved oxygen concentration and nitrate nitrogen concentration during a wastewater treatment process (WWTP) can be solved. Only input and output observation information is needed and a non-linear kinetic model during the wastewater treatment process is not needed; and on the basis of the characteristic of the approximation non-linear function structure of the neural network, the neural network is used for realizing approximation of a performance evaluation index and an optimal control strategy. The on-line learning algorithm of the controller is studied and a good effect is realized. The wastewater treatment precision and stability of the controller are improved; the wastewater treatment cost is lowered; and optimal control of the wastewater treatment process is realized, so that high-efficiency and stable operation of the wastewater treatment plant can be promoted.

Description

technical field [0001] The invention relates to an optimal control method of dissolved oxygen and nitrate nitrogen in the sewage treatment process. According to the sewage treatment process of activated sludge method, it can be seen that the control of sewage treatment is to control the main control variables dissolved oxygen and nitrate nitrogen in sewage so as to achieve the purpose of reaching the water quality of sewage treatment effluent. To improve the control performance of the sewage treatment process and promote energy saving and consumption reduction in the sewage treatment process has always been the goal of the research on intelligent control of the sewage treatment process. Optimal control of nonlinear systems is the focus of research in the field of control. The sewage treatment system is a large-scale nonlinear system, which is easily affected by the disturbance of influent flow, heavy sludge load and uncertain mixed composition in the influent sewage. feature...

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Problems solved by technology

[0002] As of the end of March 2016, a total of 3,910 sewage treatment plants have been built in cities and counties across the country, with a daily sewage treatment capacity of 167 million cubic meters. However, the operation of sewage treatment is not optimistic. The main problem is: large power consumption during sewage treatment , high operating costs, resulting in sewage treatment plants that cannot afford to be built

Traditionally, PID control is used to control the sewage treatment process in sewage plants. However, PID control cannot adapt to large time-varying situations due to its fixed gain scheduling value, and is limited by parameter adjustment. The control precision of sewage treatment is low, the error is large, and the anti-interference ability is weak Therefore, based on the system characteristics of highly nonlinear, large time-varying, large lag, and severe interference in sewage treatment, research intelligent optimal control methods for sewage treatment, improve the precision of sewage control, ensure that sewage water quality meets standards, and enable the system to run smoothly and efficiently , has become an important topic in the field of sewage process control,

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