Method for controlling input amount of tap water flocculating agent

Abstract

The invention discloses a method for controlling input amount of a tap water flocculating agent. The method comprises the steps of obtaining a feedforwad predicted value for the input amount of the flocculating agent through multi-factor feedforward learning prediction of an artificial nerve network, then testing a correspondence curve between flocculating agent adding lag time and water source flow through a reaction curve method, and recording corresponding data every certain time period; searching data which correspond with a (K-1) time point and a (K-2) time point which are related with a K time point, and obtaining three sets of mutually related data; and applying three sets of obtained data into a PID control algorithm, thereby forming a large-lag PID control algorithm for adjusting the feedforward predicted value, and realizing automatic control for the input amount of the tap water flocculating agent. According to the method of the invention, adjustment calculation is performed on the feedforward predicted value through the large-lag PID control algorithm, thereby greatly improving accuracy of the input amount of the flocculating agent, improving control precision for water turbidity before filtering, reducing control residual error, ensuring safe production and smooth operation in a water industry, and realizing energy saving, consumption reduction, personnel number reduction and benefit increase.

Description

technical field [0001] The invention belongs to the technical field of controlling the dosage of liquid flocculant in the chemical addition and purification process of tap water production industry, and specifically relates to the control of dosage of flocculant in tap water based on the combination of multi-factor feedforward and multi-loop large-delay feedback algorithm method. Background technique [0002] The large lag process refers to the influence of the adjustment parameters on the adjusted parameters during the production process. The lag time is extremely long, and sometimes the lag time even reaches 1-2 hours. The automation of this ultra-long lag process is a difficult problem in itself, and if the lag time also changes with a certain parameter, it will increase the difficulty of automation. [0003] The purification process of tap water production and dosing is a multi-factor, non-linear open system, and it is also a typical large-delay and variable-delay syste...

AI Technical Summary

Problems solved by technology

From a large number of application practices, the effect of the feedforward part of the control algorithm is relatively good, and it can ensure that the turbidity of the sedimentation water is controlled within a certain range under the condition of a relatively large change in the source water parameters; while the fuzzy feedback control operation effect is general, in Under the condition that there is no change in the source water parameters, the function should be controlled by fuzzy feedback at this time, but after a long period of operation, the residual difference between the set value and the actual value of the sediment water is still relatively large (1-2 degrees about)

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