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Multi-objective real-time optimization control method for sewage treatment process

A technology for optimal control and sewage treatment, applied in water treatment parameter control, biological water/sewage treatment, biological treatment adjustment methods, etc., can solve problems such as difficult establishment of mathematical models, uncertain interference, nonlinearity, etc., and achieve economical operation cost, promotion of emissions compliance, and performance-enhancing effects

Active Publication Date: 2017-05-24
BEIJING UNIV OF TECH
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Sewage treatment is a complex industrial system involving many physical and microbial biochemical reactions, which has the characteristics of obvious nonlinearity, time-varying, and serious uncertain interference. Moreover, it is difficult to establish an accurate mathematical model for the sewage treatment process, which makes the sewage treatment process There are many difficult problems in control and optimization
The essence of the sewage treatment process is a multi-objective optimization control problem. However, the optimization model of the sewage treatment process has not been established. How to balance the relationship between energy consumption and effluent quality is of great significance to ensure the efficient and stable operation of the sewage process

Method used

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  • Multi-objective real-time optimization control method for sewage treatment process
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  • Multi-objective real-time optimization control method for sewage treatment process

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Experimental program
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Embodiment Construction

[0043] (1) Select a variable related to both energy consumption and effluent water quality: aerobic terminal dissolved oxygen S O , nitrate nitrogen S at the end of anaerobic NO , effluent mixed solid suspended matter MLSS, effluent ammonia nitrogen S NH ;

[0044] (2) Establish a model of energy consumption and effluent water quality based on the radial basis kernel function:

[0045]

[0046]

[0047] Among them, f 1 (t) and f 2 (t) are the energy consumption and effluent water quality models at time t respectively, w 10 (t) and w 20 (t) is the objective function f 1 (t) and f 2 (t) output offset, the initial value is 0.68 and 1.79, w 1n (t) and w 2n (t) is the objective function f 1 (t) and f 2 (t) The weight of the radial basis kernel function, the initial value is -0.53 and 2.42, υ(t) is the objective function f 1 (t) and f 2 (t) common input variable, υ(t)=[S O (t), S NO (t), MLSS(t), S NH (t)], the initial value is [1.9, 0.85, 15.6, 2.45], c 1n (t...

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Abstract

In allusion to the characteristics that in a sewage treatment process, the effluent water quality cannot reach the standard, the energy consumption is relatively high and the like, the invention provides a multi-objective real-time optimization control method for the sewage treatment process, by which optimization control over concentrations of dissolved oxygen SO and nitrate nitrogen SNO are achieved in the sewage treatment process. According to the optimization control method, an established energy consumption model and an established effluent water quality model, which are based on radial basis functions, are used as optimized objective functions, the optimized objective functions are treated via a multi-objective particle swarm algorithm to obtain optimized set values of the dissolved oxygen SO and the nitrate nitrogen SNO, and tracking control is performed on the optimized set values of the dissolved oxygen SO and the nitrate nitrogen SNO through a fuzzy neural network. According to the optimization control method, the problem of multi-objective real-time optimization control over the sewage treatment process is solved, the energy consumption is reduced on the basis that the effluent water quality is ensured, and high-efficiency and stable operation of a sewage treatment plant is promoted.

Description

technical field [0001] The present invention utilizes the method based on multi-objective particle swarm algorithm and fuzzy neural network to realize dissolved oxygen S O and nitrate nitrogen S NO Real-time optimal control of concentration, dissolved oxygen S O and nitrate nitrogen S NO The concentration not only determines the effluent water quality, but also has an important impact on energy consumption. The optimal control method based on multi-objective particle swarm algorithm and fuzzy neural network is applied to the time-varying sewage treatment system, and the dissolved oxygen S O and nitrate nitrogen S NO The real-time optimization control of the concentration can not only save operating costs, but also promote the discharge of sewage treatment plants to meet the standards and ensure efficient and stable operation. It is an important branch of the advanced manufacturing technology field, which belongs to both the control field and the water treatment field. Ba...

Claims

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Application Information

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IPC IPC(8): C02F3/00G06N3/00G06N3/04
CPCG06N3/006C02F3/006C02F2209/15C02F2209/22C02F2209/001G06N3/043
Inventor 韩红桂张璐乔俊飞
Owner BEIJING UNIV OF TECH
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