Sewage treatment process prediction control method based on extreme learning machine (ELM)

Abstract

Aiming at the defects in the existing sewage treatment control technology, the invention discloses a prediction control method based on an extreme learning machine (ELM). The method provided by the invention comprises the following stepsthatsewage process data are collected, an extreme learning machine is used for establishing a system model containing dissolved oxygen and nitrate nitrogen in thesewage process, the real-time state of the system is accurately described, a predictive control algorithm is adopted for rolling optimization, a control target and various constraints are embodied inan optimization performance index, and the model is updated on line according to real-time data. The flow optimization control of the sewage treatment process is realized, the control quantity can beadjusted in time according to the control condition, the stability of the control process is ensured, and the self-adaptive optimization control can be carried out according to the change condition ofthe process, so that the energy consumption of the sewage treatment process is reduced. The extreme learning machine is used as a prediction model of prediction control, so that the generalization ofthe system is improved, a local optimal solution is avoided, the model prediction speed is increased, and the calculation time is shorter when relatively high precision is obtained.

Description

technical field [0001] The invention belongs to the field of sewage treatment, and more specifically relates to a sewage treatment optimization control method and system. Background technique [0002] Sewage discharge contains a large amount of organic matter, nitrogen, phosphorus and other substances, which is the main cause of water pollution today. The stricter sewage discharge standards have also increased the control requirements for sewage treatment. However, the sewage treatment process is a complex process with strong coupling. , uncertainty, non-linearity and large lag characteristics of the complex system, after years of construction, my country's sewage treatment industry has achieved certain results, but the backward production technology and extensive management make most of the sewage treatment plants high cost and low efficiency . The most prominent performance is in relatively small sewage treatment plants, because the accuracy of the instruments is not good, ...

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Problems solved by technology

[0002] Sewage discharge contains a large amount of organic matter, nitrogen, phosphorus and other substances, which is the main cause of water pollution today. The stricter sewage discharge standards have also increased the control requirements for sewage treatment. However, the sewage treatment process is a complex process with strong coupling. , uncertainty, non-linearity and large lag characteristics of the complex system, after years of construction, my country's sewage treatment industry has achieved certain results, but the backward production technology and extensive management make most of the sewage treatment plants high cost and low efficiency

The most prominent performance is in relatively small sewage treatment plants, because the accuracy of the instruments is not good, the adjustment of equipment operation is slow, resulting in some differences in effluent quality, and the reliability and anti-interference ability is not very high

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