CN103394520A - Strip shape fuzzy control method of cold-rolled strip steel - Google Patents

Abstract

The invention provides a strip shape fuzzy control method of cold-rolled stripe steel. A working section of the outlet tension of a rolling mill and a working section of the rolling pressure of the rolling mill are divided into n branch sections respectively, and rolling conditions are classified to n2 working conditions according to all possible conditions of the different sections where the outlet tension and the rolling pressure of the rolling mill located; corresponding strip shape control fuzzy inference control models are established respectively; related fuzzy membership functions in the strip shape control fuzzy inference control models are determined by combining the physical characteristics of a roller pouring device, a working roller bending device and a middle roller bending device; strip shape fuzzy control models are established by using a Takagi-Sugeno fuzzy model establishing rule; corresponding strip shape fuzzy control models are selected according the working conditions in a rolling process to carry out on-line regulation of the roller pouring device, the working roller bending device and the middle roller bending device. The strip shape fuzzy control method of the cold-rolled stripe steel solves the technical problem that due to the fact that a conventional strip shape control method cannot obtain the high-precision regulation and control efficacy coefficient of strip shape control, strip shape defects exist in the cold-rolled strip steel products.

Description

A kind of cold-rolled strip steel shape fuzzy control method

Technical field

The invention belongs to the cold-strip steel field, relate in particular to a kind of cold-rolled strip steel shape fuzzy control method.

Background technology

In recent years, continuous expansion along with the cold-rolled steel strip products scope of application, the user is also more and more higher to the requirement of belt plate shape quality, thus the cold-rolled strip steel shape control technology become one by modern steel enterprise and large-scale research institution the emphasis research topic especially paid attention to.The principle that plate shape is controlled is to calculate each plate shape by layout board shape control algolithm to control the regulated quantity of actuator, each plate shape control measures is cooperatively interacted, farthest to eliminate the deviation between plate shape desired value and actual measured value.

Plate shape control algolithm is the core content of cold-rolled strip steel shape control system, and its superiority-inferiority has determined that directly plate shape is controlled the quality of effect.The shape of the plate based on the feedback control idea multivariable optimal control method that extensively adopts at present is by configuring the real-time Shape signal of contact plate profile instrument on-line measurement in the milling train exit, then take the quadratic sum of the deviation between plate shape desired value and real-time measurement values as the evaluation index function, each plate shape regulation device on-line control amount when cycle calculations makes this evaluation index function obtain minimum of a value.It is pointed out that the technique scheme key is that the plate shape that will obtain high-precision each plate shape regulation device is controlled the regulation and control efficiency coefficient.Yet, actual cold-rolling mill be a kind of nonlinearity, the time the complicated physical system that becomes, still can not carry out Accurate Model to it at present, this has determined that also the plate shape of high-precision each plate shape regulation device of very difficult acquisition is controlled the regulation and control efficiency coefficient, therefore can not obtain desirable plate shape and control effect.Therefore,, even modern cold rolling enterprise production line disposes state-of-the-art plate shape checkout gear, also still fail effectively to eliminate the flatness defect that cold-rolled steel strip products exists.

In order to solve the problems of the technologies described above, just must carry out from control principle the change of essence, find existing board-shape control method to have the basic reason of defect, then has the technical scheme of original innovation by proposition, effectively solve technological difficulties and the defect that the prior art scheme exists, realizing high-precision cold-rolled strip steel shape control, improve the strip shape quality of cold-rolled steel strip products, is the quality performance key effect that further improves cold-rolled steel strip products.

Summary of the invention

The object of the present invention is to provide a kind of cold-rolled strip steel shape fuzzy control method, to solve conventional board-shape control method, because the plate shape that can't obtain high-precision each plate shape regulation device is controlled the regulation and control efficiency coefficient, cause cold-rolled steel strip products to have the technical problem of flatness defect.

The present invention solves the problems of the technologies described above the technical scheme of taking to be:

1, a kind of cold-rolled strip steel shape fuzzy control method, it is characterized in that: it comprises the following steps:

Band steel for same specification, with milling train export tension force and draught pressure operation interval each evenly be divided into n subinterval, according to the institute in milling train outlet tension force and draught pressure different milling trains of living in outlet tension force subinterval and draught pressure subinterval likely situation be n with the rolling producing condition classification ²Plant operating mode; The value of n is greater than 3;

2) for said n ²Plant operating mode, set up respectively corresponding plate shape and control fuzzy reasoning control model;

3), respectively in conjunction with inclining roller arrangement physical characteristic, working-roller bending device physical characteristic, intermediate roller device physical characteristic, determine that plate shape is controlled the relevant fuzzy membership functions in fuzzy reasoning control model;

4) control fuzzy reasoning according to the plate shape that determines fuzzy membership functions and control model, utilize Takagi-Sugeno fuzzy model modeling rule to set up plate shape fuzzy control model;

5) select the incline on-line control of roller arrangement, working-roller bending device and intermediate calender rolls roll-bending device of corresponding plate shape fuzzy control model according to operation of rolling operating mode of living in.

Press such scheme, described step 2) in get n=5, one have 25 kinds of operating modes, corresponding plate shape is controlled fuzzy reasoning, and to control model specific as follows:

IFσ ₁is?S1P?and?IFσ ₂is?S2P?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₁ ⁱ,u ₁₂ ⁱ,u ₁₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2P?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₁ ⁱ,u ₂₂ ⁱ,u ₂₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2P?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₃₁ ⁱ,u ₃₂ ⁱ,u ₃₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₄₁ ⁱ,u ₄₂ ⁱ,u ₄₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₅₁ ⁱ,u ₅₂ ⁱ,u ₅₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₆₁ ⁱ,u ₆₂ ⁱ,u ₆₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2N?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₇₁ ⁱ,u ₇₂ ⁱ,u ₇₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2N?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₈₁ ⁱ,u ₈₂ ⁱ,u ₈₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2N?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₉₁ ⁱ,u ₉₂ ⁱ,u ₉₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2P?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₀₁ ⁱ,u ₁₀₂ ⁱ,u ₁₀₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2P?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₁₁₁ ⁱ,u ₁₁₂ ⁱ,u ₁₁₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2P?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₁₂₁ ⁱ,u ₁₂₂ ⁱ,u ₁₂₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₃₁ ⁱ,u ₁₃₂ ⁱ,u ₁₃₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₁₄₁ ⁱ,u ₁₄₂ ⁱ,u ₁₄₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₁₅₁ ⁱ,u ₁₅₂ ⁱ,u ₁₅₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2N?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₆₁ ⁱ,u ₁₆₂ ⁱ,u ₁₆₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2N?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₁₇₁ ⁱ,u ₁₇₂ ⁱ,u ₁₇₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2N?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₁₈₁ ⁱ,u ₁₈₂ ⁱ,u ₁₈₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2P?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₉₁ ⁱ,u ₁₉₂ ⁱ,u ₁₉₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2P?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₀₁ ⁱ,u ₂₀₂ ⁱ,u ₂₀₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2P?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₂₁₁ ⁱ,u ₂₁₂ ⁱ,u ₂₁₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₂₂₁ ⁱ,u ₂₂₂ ⁱ,u ₂₂₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₃₁ ⁱ,u ₂₃₂ ⁱ,u ₂₃₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₂₄₁ ⁱ,u ₂₄₂ ⁱ,u ₂₄₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2N?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₂₅₁ ⁱ,u ₂₅₂ ⁱ,u ₂₅₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2N?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₆₁ ⁱ,u ₂₆₂ ⁱ,u ₂₆₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2N?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₂₇₁ ⁱ,u ₂₇₂ ⁱ,u ₂₇₃ ⁱ]；

Wherein, σ ₁Single order plate shape deviation in plate shape deviation signal, S1P, S1Z, S1N be respectively describe single order plate shape deviation for just, zero, negative fuzzy number; σ ₂Second order plate shape deviation in plate shape deviation signal, S2P, S2Z, S2N be respectively describe second order plate shape deviation for just, zero, negative fuzzy number; σ ₃Quadravalence component in plate shape deviation signal, S3P, S3Z, S3N be respectively describe quadravalence plate shape deviation for just, zero, negative fuzzy number; U _iControl output vector for the roller arrangement that has a down dip in i kind operating mode, working-roller bending device and intermediate calender rolls roll-bending device on-line control amount composition; u _j1 ⁱFor the roller arrangement on-line control amount that has a down dip of j bar fuzzy rule under i kind operating mode, u _j2 ⁱFor at i kind operating mode j bar fuzzy rule bottom working roll roll-bending device on-line control amount, u _j3 ⁱFor middle roll bending device on-line control amount under i kind operating mode j bar fuzzy rule, and i=1,2 ..., 25 and j=1,2 ..., 27; u _j1 ⁱ, u _j2 ⁱAnd u _j3 ⁱCan obtain by the manually-operated Heuristics.

Press such scheme, described step 3) specifically comprises:

3.1) the roller arrangement physical characteristic is set σ in conjunction with inclining ₁Following fuzzy membership functions under i kind operating mode:

σ ₁Fuzzy membership functions f about S1P ⁱ _S1P(σ ₁):

${f^i}_{S1P}\left({\mathrm{\&sigma;}}_1\right)=\left\{\begin{array}{cc}1,& {\mathrm{\&sigma;}}_1>{\mathrm{\&alpha;}}_i\\ \frac{1}{{\mathrm{\&alpha;}}_i}{\mathrm{\&sigma;}}_i,& 0\&le;{\mathrm{\&sigma;}}_1\&le;{\mathrm{\&alpha;}}_i\\ 0,& {\mathrm{\&sigma;}}_1<0\end{array}\right.,$

Here, α _iBeing that the following single order plate of i kind operating mode shape deviation is positive threshold value, in step 2) described plate shape controls fuzzy reasoning and controls in model and think single order plate shape deviations ₁Greater than α _iShi Weizheng, less than-α _iThe time for negative, lower with;

σ ₁Fuzzy membership functions f about S1Z ⁱ _S1Z(σ ₁):

${f^i}_{S1Z}\left({\mathrm{\&sigma;}}_1\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_1>{\mathrm{\&alpha;}}_i\\ 1-\frac{1}{{\mathrm{\&alpha;}}_i}{\mathrm{\&sigma;}}_1,& 0\&le;{\mathrm{\&sigma;}}_1\&le;{\mathrm{\&alpha;}}_i\\ 1+\frac{1}{{\mathrm{\&alpha;}}_i}{\mathrm{\&sigma;}}_1,& -{\mathrm{\&alpha;}}_i\&le;{\mathrm{\&sigma;}}_1<0\\ 0,& {\mathrm{\&sigma;}}_1<-{\mathrm{\&alpha;}}_i\end{array}\right.,$

σ ₁Fuzzy membership functions f about S1N ⁱ _S1N(σ ₁):

${f^i}_{S1N}\left({\mathrm{\&sigma;}}_1\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_1>0\\ -\frac{1}{{\mathrm{\&alpha;}}_i}{\mathrm{\&sigma;}}_1,& -{\mathrm{\&alpha;}}_i\&le;{\mathrm{\&sigma;}}_1\&le;0\\ 1,& {\mathrm{\&sigma;}}_1<-{\mathrm{\&alpha;}}_i\end{array}\right.;$

3.2) set σ in conjunction with the working-roller bending device physical characteristic ₂Following fuzzy membership functions under i kind operating mode:

σ ₂Fuzzy membership functions f about S2P ⁱ _S2P(σ ₂):

${f^i}_{S2P}=\left({\mathrm{\&sigma;}}_2\right)\left\{\begin{array}{cc}1,& {\mathrm{\&sigma;}}_2>{\mathrm{\&beta;}}_i\\ \frac{1}{{\mathrm{\&beta;}}_i}{\mathrm{\&sigma;}}_2,& 0\&le;{\mathrm{\&sigma;}}_2\&le;{\mathrm{\&beta;}}_i\\ 0,& {\mathrm{\&sigma;}}_2<0\end{array}\right.,$

Here, β _iBeing that the following second order plate of i kind operating mode shape deviation is positive threshold value, in step 2) described plate shape controls fuzzy reasoning and controls in model and think second order plate shape deviations ₂Greater than β _iShi Weizheng, less than-β _iThe time for negative, lower with;

σ ₂Fuzzy membership functions f about S2Z ⁱ _S2Z(σ ₂):

${f^i}_{S2Z}\left({\mathrm{\&sigma;}}_2\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_2>{\mathrm{\&beta;}}_i\\ 1-\frac{1}{{\mathrm{\&beta;}}_i}{\mathrm{\&sigma;}}_2,& 0\&le;{\mathrm{\&sigma;}}_2\&le;{\mathrm{\&beta;}}_i\\ 1+\frac{1}{{\mathrm{\&beta;}}_i}{\mathrm{\&sigma;}}_2,& -{\mathrm{\&beta;}}_i\&le;{\mathrm{\&sigma;}}_2<0\\ 0,& {\mathrm{\&sigma;}}_2<-{\mathrm{\&beta;}}_i\end{array}\right.,$

σ ₂Fuzzy membership functions f about S2N ⁱ _S2N(σ ₂):

${f^i}_{S2N}\left({\mathrm{\&sigma;}}_2\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_2>0\\ -\frac{1}{{\mathrm{\&beta;}}_i}{\mathrm{\&sigma;}}_2,& -{\mathrm{\&beta;}}_i\&le;{\mathrm{\&sigma;}}_2\&le;0\\ 1,& {\mathrm{\&sigma;}}_2<-{\mathrm{\&beta;}}_i\end{array}\right.;$

3.3) set σ in conjunction with intermediate calender rolls roll-bending device physical characteristic ₃Following fuzzy membership functions under i kind operating mode:

σ ₃Fuzzy membership functions f about S3P ⁱ _S3P(σ ₃):

${f^i}_{S3P}\left({\mathrm{\&sigma;}}_3\right)=\left\{\begin{array}{cc}1,& {\mathrm{\&sigma;}}_3>{\mathrm{\&gamma;}}_i\\ \frac{1}{{\mathrm{\&gamma;}}_i}{\mathrm{\&sigma;}}_3,& 0\&le;{\mathrm{\&sigma;}}_3\&le;{\mathrm{\&gamma;}}_i\\ 0,& {\mathrm{\&sigma;}}_3<0\end{array}\right.,$

Here, γ _iBeing that under i kind operating mode, quadravalence plate shape deviation is positive threshold value, in step 2) described plate shape controls fuzzy reasoning and controls in model and think quadravalence plate shape deviations ₃Greater than γ _iShi Weizheng, less than-γ _iThe time for negative, lower with;

σ ₃Fuzzy membership functions f about S3Z ⁱ _S3Z(σ ₃):

${f^i}_{S3Z}\left({\mathrm{\&sigma;}}_3\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_3>{\mathrm{\&gamma;}}_i\\ 1-\frac{1}{{\mathrm{\&gamma;}}_i}{\mathrm{\&sigma;}}_3,& 0\&le;{\mathrm{\&sigma;}}_3\&le;{\mathrm{\&gamma;}}_i\\ 1+\frac{1}{{\mathrm{\&gamma;}}_i}{\mathrm{\&sigma;}}_3,& -{\mathrm{\&gamma;}}_i\&le;{\mathrm{\&sigma;}}_3<0\\ 0,& {\mathrm{\&sigma;}}_3<-{\mathrm{\&gamma;}}_i\end{array}\right.,$

σ ₃Fuzzy membership functions f about S3N ⁱ _S3N(σ ₃):

${f^i}_{S3N}\left({\mathrm{\&sigma;}}_3\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_3>0\\ -\frac{1}{{\mathrm{\&gamma;}}_i}{\mathrm{\&sigma;}}_3,& -{\mathrm{\&gamma;}}_i\&le;{\mathrm{\&sigma;}}_3\&le;0\\ 1,& {\mathrm{\&sigma;}}_3<-{\mathrm{\&gamma;}}_i\end{array}\right.$

Press such scheme, the plate shape fuzzy control model that described step 4) is set up is:

$\left[\begin{array}{ccc}{u}_{i1}& u_{i2}& u_{i2}\end{array}\right]=\underset{j=1}{\overset{27}{\mathrm{\&Sigma;}}}{h}_{\mathrm{ij}}\&times;\left[\begin{array}{ccc}{u_{j1}}^i& {u_{j2}}^i& {u_{j3}}^i\end{array}\right],$

I=1 wherein, 2 ..., 25, u _i1Be the i kind operating mode roller arrangement regulated quantity that has a down dip, u _i2Be i kind operating mode bottom working roll roll-bending device regulated quantity, u _i3It is i kind operating mode bottom working roll roll-bending device regulated quantity;

h _i1=f ⁱ _S1P(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3P(σ ₃)，h _i2=f ⁱ _S1P(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i3=f ⁱ _S1P(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3N(σ ₃)，h _i4=f ⁱ _S1P(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i5=f ⁱ _S1P(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i6=f ⁱ _S1P(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i7=f ⁱ _S1P(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3P(σ ₃)，h _i8=f ⁱ _S1P(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i9=f ⁱ _S1P(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3N(σ ₃)，h _i10=f ⁱ _S1Z(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i11=f ⁱ _S1Z(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i12=f ⁱ _S1Z(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i13=f ⁱ _S1Z(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3P(σ ₃)，h _i14=f ⁱ _S1Z(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i15=f ⁱ _S1Z(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3N(σ ₃)，h _i16=f ⁱ _S1Z(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i17=f ⁱ _S1Z(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i18=f ⁱ _S1Z(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i19=f ⁱ _S1N(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3P(σ ₃)，h _i20=f ⁱ _S1N(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i21=f ⁱ _S1N(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3N(σ ₃)，h _i22=f ⁱ _S1N(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i23=f ⁱ _S1N(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i24=f ⁱ _S1N(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i25=f ⁱ _S1N(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3P(σ ₃)，h _i26=f ⁱ _S1N(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i27=f ⁱ _S1N(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3N(σ ₃)。

Press such scheme, the concrete regulative mode of described step 5) is: the roller arrangement regulated quantity of inclining is u _i1, the working-roller bending device regulated quantity is u _i2, intermediate calender rolls roll-bending device regulated quantity is u _i3

Press such scheme, the order of regulating in described step 5) is: the principle that the transmission device faster according to response speed, that sensitivity is larger is first transferred is carried out on-line control to the roller arrangement that inclines, working-roller bending device and intermediate calender rolls roll-bending device successively.

Compared with prior art, beneficial effect of the present invention is: the use fuzzy Modeling Method has been set up the dynamic relationship between single order, second order and quadravalence plate shape deviation and the roller arrangement that inclines, working-roller bending device and intermediate calender rolls roll-bending device on-line control amount, set up plate shape fuzzy control model, realized the accurate control to cold-strip steel outlet strip shape quality; The method does not need to obtain the accurate mathematical model parameter of Cold Rolling process and strong robustness simultaneously, simple and feasible, meet the requirement of real-time that plate shape is controlled control system fully, can effectively eliminate the typical flatness defect that cold-rolled steel strip products exists, solve conventional board-shape control method and caused cold-rolled steel strip products to have the technical problem of flatness defect because the plate shape that can't obtain high-precision each plate shape regulation device is controlled the regulation and control efficiency coefficient.

Description of drawings

Fig. 1 is the flow chart of one embodiment of the invention.

Fig. 2 is the milling train exit plate shape distribution map before control method of the present invention drops into.

Fig. 3 is the milling train exit plate shape distribution map after control method of the present invention drops into.

The specific embodiment

The invention will be further described below in conjunction with the drawings and specific embodiments so that those skilled in the art the present invention may be better understood and can be implemented, but illustrated embodiment is not as a limitation of the invention.

Fig. 1 is the flow chart of one embodiment of the invention, and it comprises the following steps:

1) for the band steel of same specification, with milling train export tension force and draught pressure operation interval each evenly be divided into n subinterval, according to the institute in milling train outlet tension force and draught pressure different milling trains of living in outlet tension force subinterval and draught pressure subinterval likely situation be n with the rolling producing condition classification ²Plant operating mode; The value of n is greater than 3(because milling train outlet tension force has 3 kinds of situations, and draught pressure has 3 kinds of situations, so the operating mode sum should be greater than 3 * 3=9);

2) for said n ²Plant operating mode, set up respectively corresponding plate shape and control fuzzy reasoning control model;

3), respectively in conjunction with inclining roller arrangement physical characteristic, working-roller bending device physical characteristic, intermediate roller device physical characteristic, determine that plate shape is controlled the relevant fuzzy membership functions in fuzzy reasoning control model;

4) control fuzzy reasoning according to the plate shape that determines fuzzy membership functions and control model, utilize Takagi-Sugeno fuzzy model modeling rule to set up plate shape fuzzy control model;

5) select the incline on-line control of roller arrangement, working-roller bending device and intermediate calender rolls roll-bending device of corresponding plate shape fuzzy control model according to operation of rolling operating mode of living in.

Can be used for four rollers, six roller single chassis or multi-frame tandem mills based on cold-rolled strip steel shape thickness of slab integrated control method of the present invention.Below take a single chassis six-high cluster mill as example, but the product of six-high cluster mill rolling comprises common plate, high-strength steel, part stainless steel and silicon steel etc.The present embodiment rolling be middle high grade silicon steel, type is the UCM milling train, plate shape control device comprises that roller declination, the positive and negative roller of working roll, the positive roller of intermediate calender rolls, intermediate roll shifting and emulsion section are cooling etc.Wherein intermediate roll shifting is to preset according to strip width, and adjusting principle is that intermediate calender rolls body of roll edge is alignd with steel edge portion, also can be considered to add a correction by operation side, is transferred to a rear holding position constant; Emulsion section is cooling has larger characteristic time lag.Thereby the plate shape control device of on-line control mainly contains three kinds of roller declinations, the positive and negative roller of working roll, the positive roller of intermediate calender rolls.Basic mechanical design feature index and the device parameter of this unit are:

Mill speed: Max900m/min, draught pressure: Max18000KN, maximum rolling force square: 140.3KN * m, coiling tension: Max220KN, main motor current: 5500KW;

Supplied materials thickness range: 1.8～2.5mm, supplied materials width range: 850～1280mm, outgoing gauge scope: 0.3mm～1.0mm;

Work roll diameter: 290～340mm, working roll height: 1400mm, intermediate calender rolls diameter: 440～500mm, intermediate calender rolls height: 1640mm, backing roll diameter: 1150～1250mm, backing roll height: 1400mm;

Every side work roll bending power :-280～350KN, every side intermediate calender rolls bending roller force: 0～500KN, the axial traversing amount of intermediate calender rolls :-120～120mm, auxiliary hydraulic system pressure: 14MPa, balance bending system pressure: 28MPa, press down system pressure: 28MPa.

Plate profile instrument adopts ABB AB's plate shape roller of Sweden, the roller footpath 313mm of this plate shape roller, formed by the solid steel axle, broad ways is divided into a measured zone every 52mm or 26mm, be uniform-distribution with four grooves to place magnetoelasticity power sensor in the surrounding of measuring roller vertically in each measured zone, the outside of sensor is wrapped up by steel loop.Plate shape roller often rotates a circle, and can measure four times Strip Shape.

Particularly, the specific works process of utilizing the present embodiment inventive method to carry out the cold-rolled strip steel shape fuzzy control is:

(1) for the band steel of same specification, with milling train export tension force and draught pressure operation interval each evenly be divided into 5 subintervals, according to the institute in milling train outlet tension force and draught pressure different milling trains of living in outlet tension force subinterval and draught pressure subinterval likely situation can be 25 kinds of operating modes with the rolling producing condition classification.

(2) for the band steel of same specification, described in establishment step (1), 25 kinds of plate shapes corresponding to operating mode are controlled fuzzy reasoning and are controlled model respectively:

IFσ ₁is?S1P?and?IFσ ₂is?S2P?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₁ ⁱ,u ₁₂ ⁱ,u ₁₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2P?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₁ ⁱ,u ₂₂ ⁱ,u ₂₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2P?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₃₁ ⁱ,u ₃₂ ⁱ,u ₃₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₄₁ ⁱ,u ₄₂ ⁱ,u ₄₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₅₁ ⁱ,u ₅₂ ⁱ,u ₅₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₆₁ ⁱ,u ₆₂ ⁱ,u ₆₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2N?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₇₁ ⁱ,u ₇₂ ⁱ,u ₇₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2N?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₈₁ ⁱ,u ₈₂ ⁱ,u ₈₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2N?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₉₁ ⁱ,u ₉₂ ⁱ,u ₉₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2P?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₀₁ ⁱ,u ₁₀₂ ⁱ,u ₁₀₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2P?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₁₁₁ ⁱ,u ₁₁₂ ⁱ,u ₁₁₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2P?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₁₂₁ ⁱ,u ₁₂₂ ⁱ,u ₁₂₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₃₁ ⁱ,u ₁₃₂ ⁱ,u ₁₃₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₁₄₁ ⁱ,u ₁₄₂ ⁱ,u ₁₄₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₁₅₁ ⁱ,u ₁₅₂ ⁱ,u ₁₅₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2N?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₆₁ ⁱ,u ₁₆₂ ⁱ,u ₁₆₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2N?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₁₇₁ ⁱ,u ₁₇₂ ⁱ,u ₁₇₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2N?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₁₈₁ ⁱ,u ₁₈₂ ⁱ,u ₁₈₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2P?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₉₁ ⁱ,u ₁₉₂ ⁱ,u ₁₉₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2P?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₀₁ ⁱ,u ₂₀₂ ⁱ,u ₂₀₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2P?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₂₁₁ ⁱ,u ₂₁₂ ⁱ,u ₂₁₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₂₂₁ ⁱ,u ₂₂₂ ⁱ,u ₂₂₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₃₁ ⁱ,u ₂₃₂ ⁱ,u ₂₃₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₂₄₁ ⁱ,u ₂₄₂ ⁱ,u ₂₄₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2N?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₂₅₁ ⁱ,u ₂₅₂ ⁱ,u ₂₅₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2N?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₆₁ ⁱ,u ₂₆₂ ⁱ,u ₂₆₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2N?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₂₇₁ ⁱ,u ₂₇₂ ⁱ,u ₂₇₃ ⁱ]；

Wherein, σ ₁Single order plate shape deviation in plate shape deviation signal, unit is I, S1P, S1Z, S1N be respectively describe single order plate shape deviation for just, zero, negative fuzzy number; σ ₂Second order plate shape deviation in plate shape deviation signal, unit is I, S2P, S2Z, S2N be respectively describe second order plate shape deviation for just, zero, negative fuzzy number; σ ₃Quadravalence component in plate shape deviation signal, unit are I, S3P, S3Z, S3N be respectively describe quadravalence plate shape deviation for just, zero, negative fuzzy number; U _iControl output vector for the roller arrangement that has a down dip in i kind operating mode, working-roller bending device and intermediate calender rolls roll-bending device on-line control amount composition; u _j1 ⁱFor the roller arrangement on-line control amount that has a down dip of j bar fuzzy rule under i kind operating mode, unit is mm, u _j2 ⁱFor in i kind operating mode j bar fuzzy rule bottom working roll roll-bending device on-line control amount, unit is KN, u _j3 ⁱFor middle roll bending device on-line control amount under i kind operating mode j bar fuzzy rule, unit is KN, and i=1,2 ..., 25 and j=1,2 ..., 27; u _j1 ⁱ, u _j2 ⁱAnd u _j3 ⁱCan obtain by the manually-operated Heuristics.

(3), respectively in conjunction with inclining roller arrangement physical characteristic, working-roller bending device physical characteristic, intermediate roller device physical characteristic, determine that plate shape is controlled the relevant fuzzy membership functions in fuzzy reasoning control model.

(3.1) set σ in conjunction with the roller arrangement physical characteristic of inclining ₁Following fuzzy membership functions under i kind operating mode:

σ ₁Fuzzy membership functions f about S1P ⁱ _S1P(σ ₁):

${f^i}_{S1P}\left({\mathrm{\&sigma;}}_1\right)=\left\{\begin{array}{cc}1,& {\mathrm{\&sigma;}}_1>{\mathrm{\&alpha;}}_i\\ \frac{1}{{\mathrm{\&alpha;}}_i}{\mathrm{\&sigma;}}_i,& 0\&le;{\mathrm{\&sigma;}}_1\&le;{\mathrm{\&alpha;}}_i\\ 0,& {\mathrm{\&sigma;}}_1<0\end{array}\right.,$

Here, α _iBe that the following single order plate of i kind operating mode shape deviation is positive threshold value, unit is I, controls fuzzy reasoning the described plate shape of step (2) and thinks single order plate shape deviations in controlling model ₁Greater than α _iShi Weizheng, less than-α _iThe time for negative, lower with;

σ ₁Fuzzy membership functions f about S1Z ⁱ _S1Z(σ ₁):

${f^i}_{S1Z}\left({\mathrm{\&sigma;}}_1\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_1>{\mathrm{\&alpha;}}_i\\ 1-\frac{1}{{\mathrm{\&alpha;}}_i}{\mathrm{\&sigma;}}_1,& 0\&le;{\mathrm{\&sigma;}}_1\&le;{\mathrm{\&alpha;}}_i\\ 1+\frac{1}{{\mathrm{\&alpha;}}_i}{\mathrm{\&sigma;}}_1,& -{\mathrm{\&alpha;}}_i\&le;{\mathrm{\&sigma;}}_1<0\\ 0,& {\mathrm{\&sigma;}}_1<-{\mathrm{\&alpha;}}_i\end{array}\right.,$

σ ₁Fuzzy membership functions f about S1N ⁱ _S1N(σ ₁):

${f^i}_{S1N}\left({\mathrm{\&sigma;}}_1\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_1>0\\ -\frac{1}{{\mathrm{\&alpha;}}_i}{\mathrm{\&sigma;}}_1,& -{\mathrm{\&alpha;}}_i\&le;{\mathrm{\&sigma;}}_1\&le;0\\ 1,& {\mathrm{\&sigma;}}_1<-{\mathrm{\&alpha;}}_i\end{array}\right.;$

(3.2) set σ in conjunction with the working-roller bending device physical characteristic ₂Following fuzzy membership functions under i kind operating mode:

σ ₂Fuzzy membership functions f about S2P ⁱ _S2P(σ ₂):

${f^i}_{S2P}\left({\mathrm{\&sigma;}}_2\right)=\left\{\begin{array}{cc}1,& {\mathrm{\&sigma;}}_2>{\mathrm{\&beta;}}_i\\ \frac{1}{{\mathrm{\&beta;}}_i}{\mathrm{\&sigma;}}_2,& 0\&le;{\mathrm{\&sigma;}}_2\&le;{\mathrm{\&beta;}}_i\\ 0,& {\mathrm{\&sigma;}}_2<0\end{array}\right.,$

Here, β _iBe that the following second order plate of i kind operating mode shape deviation is positive threshold value, unit is I, controls fuzzy reasoning the described plate shape of step (2) and thinks second order plate shape deviations in controlling model ₂Greater than β _iShi Weizheng, less than-β _iThe time for negative, lower with;

σ ₂Fuzzy membership functions f about S2Z ⁱ _S2Z(σ ₂):

${f^i}_{S2Z}\left({\mathrm{\&sigma;}}_2\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_2>{\mathrm{\&beta;}}_i\\ 1-\frac{1}{{\mathrm{\&beta;}}_i}{\mathrm{\&sigma;}}_2,& 0\&le;{\mathrm{\&sigma;}}_2\&le;{\mathrm{\&beta;}}_i\\ 1+\frac{1}{{\mathrm{\&beta;}}_i}{\mathrm{\&sigma;}}_2,& -{\mathrm{\&beta;}}_i\&le;{\mathrm{\&sigma;}}_2<0\\ 0,& {\mathrm{\&sigma;}}_2<-{\mathrm{\&beta;}}_i\end{array}\right.,$

σ ₂Fuzzy membership functions f about S2N ⁱ _S2N(σ ₂):

${f^i}_{S2N}\left({\mathrm{\&sigma;}}_2\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_2>0\\ -\frac{1}{{\mathrm{\&beta;}}_i}{\mathrm{\&sigma;}}_2,& -{\mathrm{\&beta;}}_i\&le;{\mathrm{\&sigma;}}_2\&le;0\\ 1,& {\mathrm{\&sigma;}}_2<-{\mathrm{\&beta;}}_i\end{array}\right.;$

(3.3) set σ in conjunction with intermediate calender rolls roll-bending device physical characteristic ₃Following fuzzy membership functions under i kind operating mode:

σ ₃Fuzzy membership functions f about S3P ⁱ _S3P(σ ₃):

${f^i}_{S3P}\left({\mathrm{\&sigma;}}_3\right)=\left\{\begin{array}{cc}1,& {\mathrm{\&sigma;}}_3>{\mathrm{\&gamma;}}_i\\ \frac{1}{{\mathrm{\&gamma;}}_i}{\mathrm{\&sigma;}}_3,& 0\&le;{\mathrm{\&sigma;}}_3\&le;{\mathrm{\&gamma;}}_i\\ 0,& {\mathrm{\&sigma;}}_3<0\end{array}\right.,$

Here, γ _iBe that under i kind operating mode, quadravalence plate shape deviation is positive threshold value, unit is I, controls fuzzy reasoning the described plate shape of step (2) and thinks quadravalence plate shape deviations in controlling model ₃Greater than γ _iShi Weizheng, less than-γ _iThe time for negative, lower with;

σ ₃Fuzzy membership functions f about S3Z ⁱ _S3Z(σ ₃):

${f^i}_{S3Z}\left({\mathrm{\&sigma;}}_3\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_3>{\mathrm{\&gamma;}}_i\\ 1-\frac{1}{{\mathrm{\&gamma;}}_i}{\mathrm{\&sigma;}}_3,& 0\&le;{\mathrm{\&sigma;}}_3\&le;{\mathrm{\&gamma;}}_i\\ 1+\frac{1}{{\mathrm{\&gamma;}}_i}{\mathrm{\&sigma;}}_3,& -{\mathrm{\&gamma;}}_i\&le;{\mathrm{\&sigma;}}_3<0\\ 0,& {\mathrm{\&sigma;}}_3<-{\mathrm{\&gamma;}}_i\end{array}\right.,$

σ ₃Fuzzy membership functions f about S3N ⁱ _S3N(σ ₃):

${f^i}_{S3N}\left({\mathrm{\&sigma;}}_3\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_3>0\\ -\frac{1}{{\mathrm{\&gamma;}}_i}{\mathrm{\&sigma;}}_3,& -{\mathrm{\&gamma;}}_i\&le;{\mathrm{\&sigma;}}_3\&le;0\\ 1,& {\mathrm{\&sigma;}}_3<-{\mathrm{\&gamma;}}_i\end{array}\right..$

(4) utilize Takagi-Sugeno fuzzy model modeling rule to set up as lower plate shape fuzzy control model:

$\left[\begin{array}{ccc}{u}_{i1}& u_{i2}& u_{i2}\end{array}\right]=\underset{j=1}{\overset{27}{\mathrm{\&Sigma;}}}{h}_{\mathrm{ij}}\&times;\left[\begin{array}{ccc}{u_{j1}}^i& {u_{j2}}^i& {u_{j3}}^i\end{array}\right],$

I=1 wherein, 2 ..., 25; u _i1Be the i kind operating mode roller arrangement regulated quantity that has a down dip, unit is mm, u _i2Be i kind operating mode bottom working roll roll-bending device regulated quantity, unit is KN, u _i3Be i kind operating mode bottom working roll roll-bending device regulated quantity, unit is KN;

h _i1=f ⁱ _S1P(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3P(σ ₃)，h _i2=f ⁱ _S1P(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i3=f ⁱ _S1P(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3N(σ ₃)，h _i4=f ⁱ _S1P(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i5=f ⁱ _S1P(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i6=f ⁱ _S1P(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i7=f ⁱ _S1P(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3P(σ ₃)，h _i8=f ⁱ _S1P(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i9=f ⁱ _S1P(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3N(σ ₃)，h _i10=f ⁱ _S1Z(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i11=f ⁱ _S1Z(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i12=f ⁱ _S1Z(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i13=f ⁱ _S1Z(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3P(σ ₃)，h _i14=f ⁱ _S1Z(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i15=f ⁱ _S1Z(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3N(σ ₃)，h _i16=f ⁱ _S1Z(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i17=f ⁱ _S1Z(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i18=f ⁱ _S1Z(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i19=f ⁱ _S1N(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3P(σ ₃)，h _i20=f ⁱ _S1N(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i21=f ⁱ _S1N(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3N(σ ₃)，h _i22=f ⁱ _S1N(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i23=f ⁱ _S1N(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i24=f ⁱ _S1N(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i25=f ⁱ _S1N(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3P(σ ₃)，h _i26=f ⁱ _S1N(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i27=f ⁱ _S1N(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3N(σ ₃)。

(5) select the incline on-line control of roller arrangement, working-roller bending device and intermediate calender rolls roll-bending device of corresponding plate shape fuzzy control model according to operation of rolling operating mode of living in.The specific embodiment is: the roller arrangement regulated quantity of inclining is u _i1, the working-roller bending device regulated quantity is u _i2, intermediate calender rolls roll-bending device regulated quantity is u _i3The principle of according to fast response time, transmission device that sensitivity is large, first transferring especially, is carried out on-line control to the roller arrangement that inclines, working-roller bending device and intermediate calender rolls roll-bending device successively.

Milling train exit plate shape distribution map before the control method of the present invention that provided Fig. 2 puts into operation, adopt regulative mode manually to carry out cold-rolled strip steel shape control this moment.As seen from Figure 2, the plate shape deviation maximum of milling train exit plate shape has surpassed 10I, has very significantly flatness defect, has affected product quality and economic benefit; This has also illustrated the necessity of actual production to advanced plate shape control technology research and development.Milling train exit plate shape distribution map after Fig. 3 has provided control method of the present invention and puts into operation.As seen from Figure 3, the method for the invention has effectively been eliminated plate shape deviation, and the plate shape deviation Maximum constraint of milling train exit plate shape in 8I, has significantly improved belt steel product exit plate shape, has improved the strip shape quality of band.

Above embodiment only is used for illustrating that technological thought of the present invention and characteristics, its purpose are to make those skilled in the art can understand content of the present invention and implement according to this.The scope of the claims of the present invention is not limited to above-described embodiment, and the disclosed principle of all foundations, equivalent variations or the modification that design philosophy is done, all within the scope of the claims of the present invention.

Claims (6)

1. cold-rolled strip steel shape fuzzy control method, it is characterized in that: it comprises the following steps:

1) for the band steel of same specification, with milling train export tension force and draught pressure operation interval each evenly be divided into n subinterval, according to the institute in milling train outlet tension force and draught pressure different milling trains of living in outlet tension force subinterval and draught pressure subinterval likely situation be n with the rolling producing condition classification ²Plant operating mode; The value of n is greater than 3;

2) for said n ²Plant operating mode, set up respectively corresponding plate shape and control fuzzy reasoning control model;

3), respectively in conjunction with inclining roller arrangement physical characteristic, working-roller bending device physical characteristic, intermediate roller device physical characteristic, determine that plate shape is controlled the relevant fuzzy membership functions in fuzzy reasoning control model;

4) control fuzzy reasoning according to the plate shape that determines fuzzy membership functions and control model, utilize Takagi-Sugeno fuzzy model modeling rule to set up plate shape fuzzy control model;

5) select the incline on-line control of roller arrangement, working-roller bending device and intermediate calender rolls roll-bending device of corresponding plate shape fuzzy control model according to operation of rolling operating mode of living in.

2. a kind of cold-rolled strip steel shape fuzzy control method according to claim 1 is characterized in that: get n=5 described step 2), one have 25 kinds of operating modes, corresponding plate shape is controlled fuzzy reasoning, and to control model specific as follows:

IFσ ₁is?S1P?and?IFσ ₂is?S2P?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₁ ⁱ,u ₁₂ ⁱ,u ₁₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2P?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₁ ⁱ,u ₂₂ ⁱ,u ₂₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2P?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₃₁ ⁱ,u ₃₂ ⁱ,u ₃₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₄₁ ⁱ,u ₄₂ ⁱ,u ₄₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₅₁ ⁱ,u ₅₂ ⁱ,u ₅₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₆₁ ⁱ,u ₆₂ ⁱ,u ₆₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2N?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₇₁ ⁱ,u ₇₂ ⁱ,u ₇₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2N?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₈₁ ⁱ,u ₈₂ ⁱ,u ₈₃ ⁱ]；

IFσ ₁is?S1P?and?IFσ ₂is?S2N?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₉₁ ⁱ,u ₉₂ ⁱ,u ₉₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2P?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₀₁ ⁱ,u ₁₀₂ ⁱ,u ₁₀₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2P?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₁₁₁ ⁱ,u ₁₁₂ ⁱ,u ₁₁₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2P?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₁₂₁ ⁱ,u ₁₂₂ ⁱ,u ₁₂₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₃₁ ⁱ,u ₁₃₂ ⁱ,u ₁₃₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₁₄₁ ⁱ,u ₁₄₂ ⁱ,u ₁₄₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₁₅₁ ⁱ,u ₁₅₂ ⁱ,u ₁₅₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2N?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₆₁ ⁱ,u ₁₆₂ ⁱ,u ₁₆₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2N?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₁₇₁ ⁱ,u ₁₇₂ ⁱ,u ₁₇₃ ⁱ]；

IFσ ₁is?S1Z?and?IFσ ₂is?S2N?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₁₈₁ ⁱ,u ₁₈₂ ⁱ,u ₁₈₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2P?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₁₉₁ ⁱ,u ₁₉₂ ⁱ,u ₁₉₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2P?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₀₁ ⁱ,u ₂₀₂ ⁱ,u ₂₀₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2P?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₂₁₁ ⁱ,u ₂₁₂ ⁱ,u ₂₁₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₂₂₁ ⁱ,u ₂₂₂ ⁱ,u ₂₂₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₃₁ ⁱ,u ₂₃₂ ⁱ,u ₂₃₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2Z?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₂₄₁ ⁱ,u ₂₄₂ ⁱ,u ₂₄₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2N?and?IFσ ₃is?S3P?and,THEN?U _i=[u ₂₅₁ ⁱ,u ₂₅₂ ⁱ,u ₂₅₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2N?and?IFσ ₃is?S3Z?and,THEN?U _i=[u ₂₆₁ ⁱ,u ₂₆₂ ⁱ,u ₂₆₃ ⁱ]；

IFσ ₁is?S1N?and?IFσ ₂is?S2N?and?IFσ ₃is?S3N?and,THEN?U _i=[u ₂₇₁ ⁱ,u ₂₇₂ ⁱ,u ₂₇₃ ⁱ]；

Wherein, σ ₁Single order plate shape deviation in plate shape deviation signal, S1P, S1Z, S1N be respectively describe single order plate shape deviation for just, zero, negative fuzzy number; σ ₂Second order plate shape deviation in plate shape deviation signal, S2P, S2Z, S2N be respectively describe second order plate shape deviation for just, zero, negative fuzzy number; σ ₃Quadravalence component in plate shape deviation signal, S3P, S3Z, S3N be respectively describe quadravalence plate shape deviation for just, zero, negative fuzzy number; U _iControl output vector for the roller arrangement that has a down dip in i kind operating mode, working-roller bending device and intermediate calender rolls roll-bending device on-line control amount composition; u _j1 ⁱFor the roller arrangement on-line control amount that has a down dip of j bar fuzzy rule under i kind operating mode, u _j2 ⁱFor at i kind operating mode j bar fuzzy rule bottom working roll roll-bending device on-line control amount, u _j3 ⁱFor middle roll bending device on-line control amount under i kind operating mode j bar fuzzy rule, and i=1,2 ..., 25 and j=1,2 ..., 27; u _j1 ⁱ, u _j2 ⁱAnd u _j3 ⁱCan obtain by the manually-operated Heuristics.

3. a kind of cold-rolled strip steel shape fuzzy control method according to claim 2, it is characterized in that: described step 3) specifically comprises:

3.1) the roller arrangement physical characteristic is set σ in conjunction with inclining ₁Following fuzzy membership functions under i kind operating mode:

σ ₁Fuzzy membership functions f about S1P ⁱ _S1P(σ ₁):

Here, α _iBeing that the following single order plate of i kind operating mode shape deviation is positive threshold value, in step 2) described plate shape controls fuzzy reasoning and controls in model and think single order plate shape deviations ₁Greater than α _iShi Weizheng, less than-α _iThe time for negative, lower with;

σ ₁Fuzzy membership functions f about S1Z ⁱ _S1Z(σ ₁):

σ ₁Fuzzy membership functions f about S1N ⁱ _S1N(σ ₁):

3.2) set σ in conjunction with the working-roller bending device physical characteristic ₂Following fuzzy membership functions under i kind operating mode:

σ ₂Fuzzy membership functions f about S2P ⁱ _S2P(σ ₂):

Here, β _iBeing that the following second order plate of i kind operating mode shape deviation is positive threshold value, in step 2) described plate shape controls fuzzy reasoning and controls in model and think that second order plate shape deviations 2 is greater than β _iShi Weizheng, less than-β _iThe time for negative, lower with;

σ ₂Fuzzy membership functions f about S2Z ⁱ _S2Z(σ ₂):

σ ₂Fuzzy membership functions f about S2N ⁱ _S2N(σ ₂):

3.3) set σ in conjunction with intermediate calender rolls roll-bending device physical characteristic ₃Following fuzzy membership functions under i kind operating mode:

σ ₃Fuzzy membership functions f about S3P ⁱ _S3P(σ ₃):

Here, γ _iBeing that under i kind operating mode, quadravalence plate shape deviation is positive threshold value, in step 2) described plate shape controls fuzzy reasoning and controls in model and think quadravalence plate shape deviations ₃Greater than γ _iShi Weizheng, less than-γ _iThe time for negative, lower with;

σ ₃Fuzzy membership functions f about S3Z ⁱ _S3Z(σ ₃):

σ ₃Fuzzy membership functions f about S3N ⁱ _S3N(σ ₃):

。

4. a kind of cold-rolled strip steel shape fuzzy control method according to claim 3 is characterized in that: the plate shape fuzzy control model that described step 4) is set up is:

I=1 wherein, 2 ..., 25, u _i1Be the i kind operating mode roller arrangement regulated quantity that has a down dip, u _i2Be i kind operating mode bottom working roll roll-bending device regulated quantity, u _i3It is i kind operating mode bottom working roll roll-bending device regulated quantity;

h _i1=f ⁱ _S1P(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3P(σ ₃)，h _i2=f ⁱ _S1P(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i3=f ⁱ _S1P(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3N(σ ₃)，h _i4=f ⁱ _S1P(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i5=f ⁱ _S1P(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i6=f ⁱ _S1P(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i7=f ⁱ _S1P(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3P(σ ₃)，h _i8=f ⁱ _S1P(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i9=f ⁱ _S1P(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3N(σ ₃)，h _i10=f ⁱ _S1Z(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i11=f ⁱ _S1Z(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i12=f ⁱ _S1Z(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i13=f ⁱ _S1Z(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3P(σ ₃)，h _i14=f ⁱ _S1Z(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i15=f ⁱ _S1Z(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3N(σ ₃)，h _i16=f ⁱ _S1Z(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i17=f ⁱ _S1Z(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i18=f ⁱ _S1Z(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i19=f ⁱ _S1N(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3P(σ ₃)，h _i20=f ⁱ _S1N(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i21=f ⁱ _S1N(σ ₁)×f ⁱ _S2P(σ ₂)×f ⁱ _S3N(σ ₃)，h _i22=f ⁱ _S1N(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3P(σ ₃)，

h _i23=f ⁱ _S1N(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3Z(σ ₃)，h _i24=f ⁱ _S1N(σ ₁)×f ⁱ _S2Z(σ ₂)×f ⁱ _S3N(σ ₃)，

h _i25=f ⁱ _S1N(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3P(σ ₃)，h _i26=f ⁱ _S1N(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3Z(σ ₃)，

h _i27=f ⁱ _S1N(σ ₁)×f ⁱ _S2N(σ ₂)×f ⁱ _S3N(σ ₃)。

5. a kind of cold-rolled strip steel shape fuzzy control method according to claim 4, it is characterized in that: the concrete regulative mode of described step 5) is: the roller arrangement regulated quantity of inclining is u _i1, the working-roller bending device regulated quantity is u _i2, intermediate calender rolls roll-bending device regulated quantity is u _i3

6. a kind of cold-rolled strip steel shape fuzzy control method according to claim 1 or 5, it is characterized in that: the order of regulating in described step 5) is: the principle that the transmission device faster according to response speed, that sensitivity is larger is first transferred is carried out on-line control to the roller arrangement that inclines, working-roller bending device and intermediate calender rolls roll-bending device successively.

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