A Dissolved Oxygen Model Predictive Control Method Based on Adaptive Fuzzy Neural Network

Abstract

The present invention provides a dissolved oxygen model prediction control method based on an adaptive fuzzy neural network which achieves accurate online control of the dissolved oxygen (DO) concentration in a sewage disposal process. For features that an accurate mathematic model cannot be established and the DO concentration is difficult to control due to the nondeterminacy, the nonlinearity and the strong coupling in the sewage disposal process, the control method adaptively regulates parameters of the neural network to improve the processing capacity of the neural network, and establishesa prediction model based on the fuzzy neural network and employs a model prediction control method for control so as to improve the control effect; and the problem is solved that current adaptive capacity is poor based on switching control and PID control. The experimental result shows that: the method is good in adaptive capacity, can achieve the purpose of accurate online control of the DO concentration, can improve the effect of sewage processing and can reduce the energy consumption.

Description

technical field [0001] The invention utilizes a model predictive control method based on an adaptive fuzzy neural network to realize the control of DO concentration in the process of sewage treatment, and the control effect of DO concentration directly affects the effluent quality and energy consumption of sewage treatment plants. Precise on-line control of dissolved oxygen DO concentration in sewage treatment system can not only improve sewage treatment effect, but also reduce operating energy consumption and cost. The precise online control of dissolved oxygen DO concentration belongs to both the field of water treatment and the field of intelligent control. Background technique [0002] In recent years, the problem of shortage of water resources has become increasingly serious. At the same time, the water quality is poor and eutrophication occurs frequently. The "2017 China Environmental Status Bulletin" issued by the Ministry of Environmental Protection of China pointed...

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Problems solved by technology

[0006] The present invention obtains a dissolved oxygen model predictive control method based on an adaptive fuzzy neural network, the controller is based on an adaptive fuzzy neural network, builds a sewage treatment process model, changes the neural network parameters in real time, and utilizes the model predictive control method to achieve The purpose of precise online control of dissolved oxygen DO concentration; solve the problem of automatic adjustment of the controller according to the environment; improve the accuracy of online control of dissolved oxygen DO concentration; reduce operating energy consumption;

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