Control method for sewage treatment process based on self-organizing neural network

Abstract

The invention discloses a control method for sewage processing process based on the self-organizing neural network, and belongs to the fields of water treatment and intelligent information control. The method mainly comprises adjustment for fuzzy rules by a self-organizing mechanism and self-adaptive learning control of T-S fuzzy neural network. The method comprises the steps that comparison is carried out on the basis of a T-S fuzzy neural network controller; self-organizing adjustment is carried out on the fuzzy mechanism; self-adaptive learning of the neural network is carried out; and the fuzzy rule m at the time k is obtained, and the sewage treatment process at the time k is controlled. The method can be used to adjust the internal structure of the controller in real time according to the environment state, and an object is controlled stably. The self-organizing mechanism is used to adjust the controller structure in real time so that the controller can satisfy environment requirements more effectively; the intelligent control method can be used to control the sewage treatment process stably, so that the quality of output water meet the discharge standard; and the defect that a controller of a fixed network structure is low in environment adaptability is overcome.

Description

technical field [0001] Aiming at the problem that the sewage treatment process is easily affected by environmental changes, the invention uses the self-organized T-S fuzzy neural network method on the BSM1 platform to control the dissolved oxygen concentration and the nitrate nitrogen concentration in the sewage treatment process. T-S fuzzy neural network is a kind of neural network, which belongs to the field of intelligent information processing technology. The self-organizing neural network can adjust its internal structure according to the actual situation, so as to adapt to the change of the environment. The sewage treatment control technology based on the self-organized T-S fuzzy neural network belongs not only to the field of water treatment, but also to the field of intelligent information control. Background technique [0002] Due to the rapid development of high-tech in today's society and the blind pursuit of interests, the water resource environment has been ove...

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Problems solved by technology

[0004] Although the traditional PID control method is widely used in various industrial fields, because the sewage treatment process is a complex system with the characteristics of high nonlinearity, large lag, large time variation, and multivariable coupling, the traditional PID control method When applied to such complex systems, problems of poor robustness, low control precision and inability to adjust parameters online in real time are prone to occur, resulting in unsatisfactory control effects

Due to the fixed internal structure of the traditional neural network intelligent control method, it is difficult to respond to changes in the environment in a timely manner, resulting in unsatisfactory control effects

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