CN103394520B - 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 cold-strip steel field, particularly relate to a kind of cold-rolled strip steel shape fuzzy control method.

Background technology

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

Strip Shape Control algorithm is the core content of cold-rolled strip steel shape control system, and its superiority-inferiority directly determines the quality of Strip Shape Control effect.The plate shape Multi-variables optimum design control method based on feedback control idea extensively adopted at present is by configuring the real-time Shape signal of contact plate profile instrument on-line measurement in milling train exit, then with the quadratic sum of the deviation between plate shape desired value and real-time measurement values for 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 technique scheme key is the Strip Shape Control regulation and control efficiency coefficient that will obtain high-precision each plate shape regulation device.But, actual cold-rolling mill be a kind of nonlinearity, time become complicated physical system, still can not carry out Accurate Model to it at present, this also determines the Strip Shape Control regulation and control efficiency coefficient being difficult to obtain high-precision each plate shape regulation device, therefore can not obtain desirable Strip Shape Control effect.Therefore, even if modern cold rolling enterprise production line is configured with state-of-the-art flatness detection device, 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, the change of essence just must be carried out from control principle, find the basic reason of existing board-shape control method existing defects, then by proposing the technical scheme with original innovation, the technological difficulties that effective solution prior art scheme exists and defect, realize high-precision cold-rolled strip steel shape to control, improve the strip shape quality of cold-rolled steel strip products, for the quality improving cold-rolled steel strip products further plays key effect.

Summary of the invention

The object of the present invention is to provide a kind of cold-rolled strip steel shape fuzzy control method, cause cold-rolled steel strip products to there is the technical problem of flatness defect to solve conventional board-shape control method due to the Strip Shape Control regulation and control efficiency coefficient of high-precision each plate shape regulation device cannot be obtained.

The present invention for solving the problems of the technologies described above taked technical scheme is:

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

For the band steel of same specification, milling train is exported the operation interval of tension force and draught pressure is each is evenly divided into n subinterval, according to milling train outlet tension force subinterval different residing for milling train outlet tension force and draught pressure and draught pressure subinterval institute likely situation be n by rolling producing condition classification ²plant operating mode; The value of n is greater than 3;

2) for said n ²plant operating mode, set up corresponding Strip Shape Control fuzzy reasoning Controlling model respectively;

3) combine incline roller arrangement physical characteristic, working-roller bending device physical characteristic, intermediate roller device physical characteristic respectively, determine the dependent blur membership function in Strip Shape Control fuzzy reasoning Controlling model;

4) according to the Strip Shape Control fuzzy reasoning Controlling model determining fuzzy membership functions, Takagi-Sugeno fuzzy model modeling rule is utilized to set up plate shape fuzzy control model;

5) corresponding plate shape fuzzy control model is selected to carry out inclining the on-line control of roller arrangement, working-roller bending device and intermediate calender rolls roll-bending device according to operating mode residing for the operation of rolling.

By such scheme, described step 2) in get n=5, then one have 25 kinds of operating modes, corresponding Strip Shape Control fuzzy reasoning Controlling model is 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 be 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 be just, zero, negative fuzzy number; σ ₃four order components in plate shape deviation signal, S3P, S3Z, S3N be respectively describe quadravalence plate shape deviation be just, zero, negative fuzzy number; U _ifor the control output vector of the roller arrangement that has a down dip i-th kind of operating mode, working-roller bending device and intermediate calender rolls roll-bending device on-line control amount composition; u _j1 ⁱfor under i-th kind of operating mode, jth bar fuzzy rule has a down dip roller arrangement on-line control amount, u _j2 ⁱfor i-th kind of operating mode jth bar fuzzy rule bottom working roll roll-bending device on-line control amount, u _j3 ⁱfor intermediate calender rolls roll-bending device on-line control amount under i-th kind of operating mode jth bar fuzzy rule, and i=1,2 ..., 25 and j=1,2 ..., 27; u _j1 ⁱ, u _j2 ⁱand u _j3 ⁱcan be obtained by manual operation Heuristics.

By such scheme, described step 3) specifically comprises:

3.1) the roller arrangement physical characteristic setting σ that inclines is combined ₁following fuzzy membership functions under i-th kind of operating mode:

σ ₁about the fuzzy membership functions f of 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 i-th kind of operating mode following single order plate shape deviation be positive threshold value, in step 2) think single order plate shape deviations in described Strip Shape Control fuzzy reasoning Controlling model ₁be greater than α _ishi Weizheng, is less than-α _itime be negative, lower with;

σ ₁about the fuzzy membership functions f of 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 ₁about the fuzzy membership functions f of 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) in conjunction with working-roller bending device physical characteristic setting σ ₂following fuzzy membership functions under i-th kind of operating mode:

σ ₂about the fuzzy membership functions f of 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 i-th kind of operating mode following second order plate shape deviation be positive threshold value, in step 2) think second order plate shape deviations in described Strip Shape Control fuzzy reasoning Controlling model ₂be greater than β _ishi Weizheng, is less than-β _itime be negative, lower with;

σ ₂about the fuzzy membership functions f of 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 ₂about the fuzzy membership functions f of 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) in conjunction with intermediate calender rolls roll-bending device physical characteristic setting σ ₃following fuzzy membership functions under i-th kind of operating mode:

σ ₃about the fuzzy membership functions f of 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-th kind of operating mode, quadravalence plate shape deviation is positive threshold value, in step 2) think quadravalence plate shape deviations in described Strip Shape Control fuzzy reasoning Controlling model ₃be greater than γ _ishi Weizheng, is less than-γ _itime be negative, lower with;

σ ₃about the fuzzy membership functions f of 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 ₃about the fuzzy membership functions f of S3N ⁱ _s3N(σ ₃):

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

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

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

Wherein i=1,2 ..., 25, u _i1be that i-th kind of operating mode has a down dip roller arrangement regulated quantity, u _i2be i-th kind of operating mode bottom working roll roll-bending device regulated quantity, u _i3be i-th kind of 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)。

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

By such scheme, the order regulated in described step 5) is: the principle that the transmission device that, sensitivity faster according to response speed is larger is first adjusted carries 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: use fuzzy Modeling Method to establish single order, second order and quadravalence plate shape deviation and the roller arrangement that inclines, dynamic relationship between working-roller bending device and intermediate calender rolls roll-bending device on-line control amount, set up plate shape fuzzy control model, achieve 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 of Strip Shape Control control system completely, effectively can eliminate the typical flatness defect that cold-rolled steel strip products exists, solve conventional board-shape control method and cause cold-rolled steel strip products to there is the technical problem of flatness defect due to the Strip Shape Control regulation and control efficiency coefficient of high-precision each plate shape regulation device cannot be obtained.

Accompanying drawing explanation

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.

Detailed description of the invention

Below in conjunction with the drawings and specific embodiments, the invention will be further described, and to make 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, milling train is exported the operation interval of tension force and draught pressure is each is evenly divided into n subinterval, according to milling train outlet tension force subinterval different residing for milling train outlet tension force and draught pressure and draught pressure subinterval institute likely situation be n by rolling producing condition classification ²plant operating mode; The value of n is greater than 3(has 3 kinds of situations because milling train exports tension force, and draught pressure has 3 kinds of situations, and therefore operating mode sum should be greater than 3 × 3=9);

2) for said n ²plant operating mode, set up corresponding Strip Shape Control fuzzy reasoning Controlling model respectively;

3) combine incline roller arrangement physical characteristic, working-roller bending device physical characteristic, intermediate roller device physical characteristic respectively, determine the dependent blur membership function in Strip Shape Control fuzzy reasoning Controlling model;

4) according to the Strip Shape Control fuzzy reasoning Controlling model determining fuzzy membership functions, Takagi-Sugeno fuzzy model modeling rule is utilized to set up plate shape fuzzy control model;

5) corresponding plate shape fuzzy control model is selected to carry out inclining the on-line control of roller arrangement, working-roller bending device and intermediate calender rolls roll-bending device according to operating mode residing for the operation of rolling.

Four rollers, six roller single chassis or multi-frame tandem mills is can be used for based on cold-rolled strip steel shape thickness of slab integrated control method of the present invention.Below for a single chassis six-high cluster mill, six-high cluster mill the product of rolling can comprise common plate, high-strength steel, part stainless steel and silicon steel etc.The present embodiment rolling be middle high grade silicon steel, type is UCM milling train, and Strip Shape Control means comprise roller declination, the positive and negative roller of working roll, the positive roller of intermediate calender rolls, intermediate roll shifting and emulsion section cooling etc.Wherein intermediate roll shifting carries out presetting according to strip width, and Adjustment principle is alignd with steel edge portion at intermediate calender rolls body of roll edge, and also can consider interpolation correction by operation side, after being transferred to position, holding position is constant; Emulsion section cooling has larger characteristic time lag.Thus the Strip Shape Control means of on-line control mainly contain roller declination, the positive and negative roller of working roll, the positive roller of intermediate calender rolls three kinds.The basic mechanical design feature index of this unit and device parameter 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, intermediate calender rolls is traversing amount :-120 ~ 120mm axially, 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, be made up of single solid steel axle, a measured zone is divided in the width direction every 52mm or 26mm, surrounding vertically at measuring roller in each measured zone is uniform-distribution with four grooves to place magnetoelasticity force snesor, the outside of sensor wrap up by steel loop.Plate shape roller often rotates a circle, and can measure four times to Strip Shape.

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

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

(2) for the band steel of same specification, the Strip Shape Control fuzzy reasoning Controlling model that described in establishment step (1), 25 kinds of operating modes are corresponding 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 be 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 be just, zero, negative fuzzy number; σ ₃four order components in plate shape deviation signal, unit is I, S3P, S3Z, S3N be respectively describe quadravalence plate shape deviation be just, zero, negative fuzzy number; U _ifor the control output vector of the roller arrangement that has a down dip i-th kind of operating mode, working-roller bending device and intermediate calender rolls roll-bending device on-line control amount composition; u _j1 ⁱfor under i-th kind of operating mode, jth bar fuzzy rule has a down dip roller arrangement on-line control amount, unit is mm, u _j2 ⁱfor i-th kind of operating mode jth bar fuzzy rule bottom working roll roll-bending device on-line control amount, unit is KN, u _j3 ⁱfor intermediate calender rolls roll-bending device on-line control amount under i-th kind of operating mode jth 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 be obtained by manual operation Heuristics.

(3) combine incline roller arrangement physical characteristic, working-roller bending device physical characteristic, intermediate roller device physical characteristic respectively, determine the dependent blur membership function in Strip Shape Control fuzzy reasoning Controlling model.

(3.1) the roller arrangement physical characteristic setting σ that inclines is combined ₁following fuzzy membership functions under i-th kind of operating mode:

σ ₁about the fuzzy membership functions f of 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 i-th kind of operating mode following single order plate shape deviation be positive threshold value, unit is I, thinks single order plate shape deviations in step (2) described Strip Shape Control fuzzy reasoning Controlling model ₁be greater than α _ishi Weizheng, is less than-α _itime be negative, lower with;

σ ₁about the fuzzy membership functions f of 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 ₁about the fuzzy membership functions f of 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) in conjunction with working-roller bending device physical characteristic setting σ ₂following fuzzy membership functions under i-th kind of operating mode:

σ ₂about the fuzzy membership functions f of 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 i-th kind of operating mode following second order plate shape deviation be positive threshold value, unit is I, thinks second order plate shape deviations in step (2) described Strip Shape Control fuzzy reasoning Controlling model ₂be greater than β _ishi Weizheng, is less than-β _itime be negative, lower with;

σ ₂about the fuzzy membership functions f of 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 ₂about the fuzzy membership functions f of 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) in conjunction with intermediate calender rolls roll-bending device physical characteristic setting σ ₃following fuzzy membership functions under i-th kind of operating mode:

σ ₃about the fuzzy membership functions f of 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-th kind of operating mode, quadravalence plate shape deviation is positive threshold value, unit is I, thinks quadravalence plate shape deviations in step (2) described Strip Shape Control fuzzy reasoning Controlling model ₃be greater than γ _ishi Weizheng, is less than-γ _itime be negative, lower with;

σ ₃about the fuzzy membership functions f of 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 ₃about the fuzzy membership functions f of 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) Takagi-Sugeno fuzzy model modeling rule is utilized to set up as lower plate shape fuzzy control model:

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

Wherein i=1,2 ..., 25; u _i1be that i-th kind of operating mode has a down dip roller arrangement regulated quantity, unit is mm, u _i2be i-th kind of operating mode bottom working roll roll-bending device regulated quantity, unit is KN, u _i3be i-th kind of 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) corresponding plate shape fuzzy control model is selected to carry out inclining the on-line control of roller arrangement, working-roller bending device and intermediate calender rolls roll-bending device according to operating mode residing for the operation of rolling.Detailed description of the invention is: roller arrangement regulated quantity of inclining is u _i1, working-roller bending device regulated quantity is u _i2, intermediate calender rolls roll-bending device regulated quantity is u _i3.Especially, the principle first adjusted according to fast response time, transmission device that sensitivity is large carries 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 gives Fig. 2 puts into operation, now adopts regulative mode manually to carry out cold-rolled strip steel shape control.As seen from Figure 2, the plate shape deviation maximum of milling train exit plate shape has exceeded 10I, has obviously flatness defect, have impact on product quality and economic benefit; This also illustrates the necessity of actual production to advanced Strip Shape Control technical research.Milling train exit plate shape distribution map after the control method of the present invention that gives Fig. 3 puts into operation.As seen from Figure 3, the method for the invention effectively eliminates plate shape deviation, and the plate shape deviation Maximum constraint of milling train exit plate shape, within 8I, significantly improves belt steel product exit plate shape, improves the strip shape quality of band.

Above embodiment, only for illustration of technological thought of the present invention and feature, its object is to enable those skilled in the art 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 all equivalent variations of doing according to disclosed principle, design philosophy or modification, all within the scope of the claims of the present invention.

Claims (6)

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

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

2) for said n ²plant operating mode, set up corresponding Strip Shape Control fuzzy reasoning Controlling model respectively;

3) combine incline roller arrangement physical characteristic, working-roller bending device physical characteristic, intermediate roller device physical characteristic respectively, determine the dependent blur membership function in Strip Shape Control fuzzy reasoning Controlling model;

4) according to the Strip Shape Control fuzzy reasoning Controlling model determining fuzzy membership functions, Takagi-Sugeno fuzzy model modeling rule is utilized to set up plate shape fuzzy control model;

5) corresponding plate shape fuzzy control model is selected to carry out inclining the on-line control of roller arrangement, working-roller bending device and intermediate calender rolls roll-bending device according to operating mode residing for the operation of rolling.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

IF σ ₁is S1N and IF σ ₂is S2N and IF σ 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 be 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 be just, zero, negative fuzzy number; σ ₃four order components in plate shape deviation signal, S3P, S3Z, S3N be respectively describe quadravalence plate shape deviation be just, zero, negative fuzzy number; U _ifor the control output vector of the roller arrangement that has a down dip i-th kind of operating mode, working-roller bending device and intermediate calender rolls roll-bending device on-line control amount composition; u _j1 ⁱfor under i-th kind of operating mode, jth bar fuzzy rule has a down dip roller arrangement on-line control amount, u _j2 ⁱfor i-th kind of operating mode jth bar fuzzy rule bottom working roll roll-bending device on-line control amount, u _j3 ⁱfor intermediate calender rolls roll-bending device on-line control amount under i-th kind of operating mode jth bar fuzzy rule, and i=1,2 ..., 25 and j=1,2 ..., 27; u _j1 ⁱ, u _j2 ⁱand u _j3 ⁱobtained by manual operation Heuristics.

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

3.1) the roller arrangement physical characteristic setting σ that inclines is combined ₁following fuzzy membership functions under i-th kind of operating mode:

σ ₁about the fuzzy membership functions f of S1P ⁱ _s1P(σ ₁):

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

Here, α _ibe i-th kind of operating mode following single order plate shape deviation be positive threshold value, in step 2) think single order plate shape deviations in described Strip Shape Control fuzzy reasoning Controlling model ₁be greater than α ⁱshi Weizheng, is less than-α _itime be negative, lower with;

σ ₁about the fuzzy membership functions f of S1Z ⁱ _s1Z(σ ₁):

${f^i}_{S1Z}\left({\mathrm{\&sigma;}}_1\right)=\left\{\begin{array}{cc}0,& {\mathrm{\&sigma;}}_1>{\mathrm{\&alpha;}}_i\\ 1-\frac{1}{{\mathrm{\&alpha;}}_i}{\mathrm{\&sigma;}}_2,& 0\&le;{\mathrm{\&sigma;}}_1\&le;{\mathrm{\&alpha;}}_i\\ 1+\frac{1}{{\mathrm{\&alpha;}}_i}{\mathrm{\&sigma;}}_1,& -{\mathrm{\&alpha;}}_i\&le;{\mathrm{\&sigma;}}_1<0\\ 0,& {\mathrm{\&sigma;}}_1<-{\mathrm{\&alpha;}}_i\end{array}\right.,$

σ ₁about the fuzzy membership functions f of 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) in conjunction with working-roller bending device physical characteristic setting σ ₂following fuzzy membership functions under i-th kind of operating mode:

σ ₂about the fuzzy membership functions f of 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 i-th kind of operating mode following second order plate shape deviation be positive threshold value, in step 2) think second order plate shape deviations in described Strip Shape Control fuzzy reasoning Controlling model ₂be greater than β _ishi Weizheng, is less than-β _itime be negative, lower with;

σ ₂about the fuzzy membership functions f of 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 ₂about the fuzzy membership functions f of 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) in conjunction with intermediate calender rolls roll-bending device physical characteristic setting σ ₃following fuzzy membership functions under i-th kind of operating mode:

σ ₃about the fuzzy membership functions f of 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-th kind of operating mode, quadravalence plate shape deviation is positive threshold value, in step 2) think quadravalence plate shape deviations in described Strip Shape Control fuzzy reasoning Controlling model ₃be greater than γ _ishi Weizheng, is less than-γ _itime be negative, lower with;

σ ₃about the fuzzy membership functions f of 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 ₃about the fuzzy membership functions f of S3N ⁱ _s3N(σ ₃):

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

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

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

Wherein i=1,2 ..., 25, u _i1be that i-th kind of operating mode has a down dip roller arrangement regulated quantity, u _i2be i-th kind of operating mode bottom working roll roll-bending device regulated quantity, u _i3be i-th kind of 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, is characterized in that: described step 5) concrete regulative mode is: roller arrangement regulated quantity of inclining is u _i1, 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, is characterized in that: described step 5) in the order that regulates be: the principle that the transmission device that, sensitivity faster according to response speed is larger is first adjusted carries out on-line control to the roller arrangement that inclines, working-roller bending device and intermediate calender rolls roll-bending device successively.