An Optimal Control Method for Sewage Treatment Process Based on Neural Network

Abstract

The invention provides a neural network based sewage disposal process optimal control method and aims to solve the problem of excessive energy consumption during a sewage disposal process. The sewage disposal process is a highly non-linear, time-varying and complicated process, and on the premise that effluent qualities meet the standard, reduction of operation energy consumption is much challenging. The method mainly includes two neural networks, wherein one neural network is used for establishing a sewage disposal process prediction model so as to achieve prediction of performance indexes, and the other neural network is used for real-timely optimizing control variable set values according to system states and predicted performance indexes. Finally, optimal control of dissolved oxygen concentration and nitrate nitrogen concentration is achieved, so that requirements of effluent qualities can met, and meanwhile, operation costs of the sewage disposal process can be effectively reduced.

Description

technical field [0001] Aiming at the problem of high energy consumption in the sewage treatment process, the invention utilizes the neural network to optimize the control of the dissolved oxygen concentration and the nitrate nitrogen concentration in the sewage treatment process in the BSM1. Neural network is one of the main branches of intelligent control technology. The optimal control of sewage treatment process based on neural network belongs not only to the field of water treatment, but also to the field of intelligent optimal control. Background technique [0002] With the continuous acceleration of urbanization and industrialization, my country's water environment has been severely damaged and has a tendency to continue to deteriorate. Sewage discharge not only seriously affects the daily life of residents, but also destroys the ecological balance of nature. In order to reduce the discharge of sewage, sewage treatment plants have been established all over the country...

AI Technical Summary

Problems solved by technology

Although the optimal control method based on model predictive control (MPC) can reduce energy consumption to a certain extent, MPC takes the system mechanism model as the core and calculates the optimal control quantity through certain mathematical means. Due to the complexity of the sewage treatment process, It is difficult to establish an accurate mathematical model, and the accuracy of the model has a great influence on the control performance, and the inability to measure some key water quality parameters online will also reduce the control performance

The optimization control method based on the genetic algorithm GA has a large amount of calculation and a slow global convergence speed, and the accuracy of the optimization result is controlled by the length of the code

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