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Sludge bulking inhibition method based on self-adaptive segmented sliding mode control

A sludge bulking and self-adaptive technology, applied in self-adaptive control, general control system, control/regulation system, etc., can solve problems such as difficult automatic monitoring and control

Active Publication Date: 2021-02-12
BEIJING UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Sludge volume index is generally determined by off-line analysis technology in the laboratory, which is difficult to carry out automatic monitoring and control

Method used

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  • Sludge bulking inhibition method based on self-adaptive segmented sliding mode control
  • Sludge bulking inhibition method based on self-adaptive segmented sliding mode control
  • Sludge bulking inhibition method based on self-adaptive segmented sliding mode control

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Embodiment Construction

[0080] The present invention obtains a method for inhibiting sludge expansion based on self-adaptive segmented sliding mode control, using the dissolved oxygen concentration in the aerobic tank, the sludge load rate in the Sludge residence time and reflux ratio predict the sludge volume index in the sewage treatment process in real time, build a multi-stage sliding mode controller to adjust the dissolved oxygen concentration and nitrate nitrogen concentration, and design a suitable switching mechanism to keep the sewage treatment process in normal working conditions. Realize the inhibition of sludge bulking;

[0081] The present invention adopts following technical scheme and implementation steps:

[0082] 1. A sludge bulking suppression method based on adaptive segmental sliding mode control,

[0083] By predicting the sludge volume index in real time and designing a suitable sliding mode controller, the sludge bulking can be suppressed. The overall structure is as follows: ...

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Abstract

The invention provides a sludge bulking inhibition method based on self-adaptive segmented sliding mode control, and aims to inhibit sludge bulking in order to solve the problems that abnormal sludgebulking working conditions are likely to occur in a sewage treatment process and are unlikely to transit to normal working conditions. According to the method of the invention, a fuzzy neural networkis adopted to obtain the water quality parameters of a sewage treatment operation process, predict a sludge volume index in real time and judge the working condition of the operation process, and provides a reference signal for the switching of a controller; and a segmented sliding mode controller with a self-adaptive switching mechanism is designed to regulate and control dissolved oxygen concentration and nitrate nitrogen concentration; and a biochemical reaction process is coordinated, the sludge settling characteristic is improved, and it can be guaranteed that the normal working conditionis recovered when sludge bulking occurs in the sewage treatment process.

Description

technical field [0001] The patent of the present invention uses the sludge expansion suppression method based on adaptive segmental sliding mode control to realize the suppression of sludge expansion in the sewage treatment process, and coordinates the biochemical reaction process by adjusting the process variables dissolved oxygen concentration and nitrate nitrogen concentration, so that the sewage treatment process The sludge volume index is an important index to measure sludge bulking, and it is of great significance to predict this index in real time during the control process; to ensure that the sewage treatment process returns to normal working conditions when sludge bulking occurs, both Belongs to the field of water research, but also belongs to the field of intelligent control; Background technique [0002] Water is the most important basic resource for urban development. In recent years, the continuous development of industry has gradually increased the discharge o...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/04
Inventor 韩红桂秦晨辉伍小龙乔俊飞
Owner BEIJING UNIV OF TECH
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