Cold rolling band steel plate shape intelligent optimization control method

Abstract

The invention provides a cold rolling band steel plate shape intelligent optimization control method. A plate shape deviation signal is divided into a left wave and right wave component, a middle wave and two-side wave component and a quarter wave and side middle wave component through model recognition. A fuzzy inference rule for cold rolling mill plate shape control is built. A generalized input variable and a generalized fuzzy subset of the variable are defined for the obtained fuzzy inference rule, and then a fuzzy membership function of a fuzzy set that the generalized input variable corresponds to is taken. Online adjusting quantity of a cold rolling mill roll inclining device, a working roll bending device and a middle roll bending device is calculated to obtain an online adjusting quantity calculation model of the cold rolling mill plate shape intelligent optimization control. Online adjustment is conducted according to the obtained online adjusting quantity calculation model. The problem of poor cold rolling band steel product plate shape control quality caused by the fact that transmission lag exists between a mill body and a plate shape instrument and affecting factors of the plate shape are not considered comprehensively is solved.

Description

technical field [0001] The invention belongs to the field of cold-rolled steel strips, in particular to an intelligent optimization control method for cold-rolled strip steel shapes. Background technique [0002] In recent years, with the continuous expansion of the scope of use of cold-rolled strip products, users have higher and higher requirements for the quality of the strip shape, so the cold-rolled strip shape control technology has become a modern steel enterprise and large research institutions. Special attention to key research topics. The principle of flatness control is to calculate the adjustment amount of each flatness control actuator by designing the flatness control algorithm, so that each flatness control means cooperate with each other, so as to eliminate the deviation between the flatness target value and the actual measured value to the greatest extent . [0003] The shape control algorithm is the core content of the cold-rolled strip shape control syst...

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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide an intelligent optimal control method for cold-rolled strip shape to solve the two reasons of the transmission time lag between the rolling mill body and the shape meter and the incomplete consideration of the factors affecting the shape The technical problem that leads to the low quality of cold-rolled strip product shape control

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