Sewage treatment control method based on self-adaptive predictive control

Abstract

The invention provides a sewage treatment control method based on self-adaptive predictive control, which comprises the following steps of acquiring real-time data in a sewage treatment process, constructing a model-free self-adaptive predictive controller according to the acquired real-time data, outputting a dissolved oxygen conversion coefficient and a real-time control value of an internal reflux quantity by utilizing the model-free self-adaptive predictive controller, according to the real-time control values of the dissolved oxygen conversion coefficient and the internal reflux quantity, controlling the nitrate nitrogen concentration and the dissolved oxygen concentration in the sewage treatment process to track the set expected values in real time, and achieiving the purpose of sewage purification. According to the method, the I / O data in the sewage treatment process are fully utilized, the design of the controller only depends on the I / O data, no model information is needed, the unmodeled dynamic problem can be avoided, the method is particularly suitable for control over the actual sewage treatment process, and effective control results can be achieved under different sewage treatment operation conditions; the problem that the existing sewage treatment method is not suitable for the actual sewage treatment industry due to no modeling dynamics is solved.

Description

technical field [0001] The invention relates to the technical field of intelligent control of sewage treatment, in particular to a sewage treatment control method based on adaptive predictive control. Background technique [0002] Urban sewage treatment is a complex nonlinear dynamic process that uses urban domestic water, industrial wastewater and rainfall through a series of biochemical reactions to make it reach the sewage discharge index. In the current sewage treatment process, the activated sludge method is the most widely used sewage treatment method. The whole sewage treatment process adopts the pre-denitrification process, and after the steps of primary sedimentation, denitrification-nitrification, and secondary precipitation, the process is completed. Treatment and purification of sewage. Among them, the nitrate nitrogen S in the second zone of the denitrification and nitrification process in the biochemical reaction pool NO,2 Concentration and five zone dissolve...

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Problems solved by technology

[0005] The methods disclosed in the above patents and similar methods in other related documents can be classified into two types. One is the control method based on the ideal mathematical model. Unforeseen problems may occur in the actual sewage treatment, and even bring huge losses to the production of the enterprise; the other is an intelligent control method that does not require an accurate model of the system. Take the fuzzy neural network method as an example. The controller design of the algorithm depends on the fuzzy rules and the neural network model of the sewage treatment process, and the establishment of the fuzzy rules and the neural network model also requires the prior knowledge of the system and a large amount of sewage operation data, and the problem of unmodeled dynamics is still unavoidable

The sewage treatment system is an uncertain and susceptible to disturbance system, so the above-mentioned patented method still has a certain degree of conservatism in the actual industrial application of the sewage treatment system

To sum up, at present, there is no key target variable S that is particularly suitable for the actual industrial process of the sewage treatment system at home and abroad. NO,2 Concentration and D O,5 A high-performance data-driven controller design method for effective concentration control without requiring precise system models and prior knowledge

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