CN1775394A - Thickness adaptive fuzzy control method for aluminium plate band rolling mill - Google Patents
Thickness adaptive fuzzy control method for aluminium plate band rolling mill Download PDFInfo
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Abstract
The present invention relates to a thickness control method of aluminium strip and sheet mill. It is characterized by that it can make traditional PID control and fuzzy control be organically combined together, utilizes the factors of thickness-measuring instrument signal and quantization factor defined by specialist to create the fuzzy relationship between thickness error and error variable rate and PID parameter regulation quantity, and adopts the following steps: utilizing fuzzy operation to obtain control table, making the thickness error obtained by measurement and variable rate of thickness error implement obfuscation, making comparison is universe of discourse, taking correspondent regulation quantity of PID parameter from control table, superimposing it on the PID control control parameter, then utilizing hydraulic system of rolling mill to set the required clearance between rolls so as to implement regulation and control of rolling mill thickness.
Description
Technical field
The present invention relates to the production of industrial aluminium strip paper tinsel, be in particular the control method of Aluminium Strip Surface milling train thickness, especially the method that adopts Intelligent Fuzzy Control to combine with traditional PID control is controlled the milling train thickness in the Aluminium Strip Surface process, belongs to technical field of nonferrous metal processing.
Background technology
In the aluminium sheet band process, the parameter of milling train thickness adjustment system and adjusting change in gain are frequent, and the operation of rolling has stronger non-linear factor, and there are shortcomings such as parameter tuning difficulty, the control quality is not good enough in conventional PID control system, and especially milling material thickness differs greatly end to end.
Fuzzy control does not rely on the mathematical models of controlled device, and suitable especially close couplings of importing having more-exporting more and parameter time varying and severe nonlinear and probabilistic complication system or process are controlled.This control method is fairly simple, and effect is good, begins to enter the plastic working field in recent years, and has obtained fast development, and the control accuracy of thickness of strip is greatly improved.
Because the simple proportional differential action of fuzzy theory controling appliance, so certainly existing steady-state error, its adaptive capacity is also lower; In addition for time lag system, because operation of rolling more complicated, the Artificial Control experience is difficult to stable the acquisition, and the control performance performance of fuzzy control also will be by means of traditional PID control, otherwise easily shakes even disperse.Therefore, thus the milling train thickness that how fuzzy control and traditional PID control is combined and control the aluminium sheet band better, and this is the important research project in this area just.
Summary of the invention
The adaptive fuzzy control method that the purpose of this invention is to provide a kind of aluminium plate band rolling mill thickness, by this fuzzy control method, the pid parameter of thickness control system is adjusted certainly in realization aluminium strip/aluminium foil production process, thereby reduces the deviation end to end of band (paper tinsel) material, improves the response speed of control system.
For realizing purpose of the present invention, thickness adaptive fuzzy control method for aluminium plate band rolling mill is characterized in that: the control method that adopts fuzzy control and traditional PI D to combine, the milling train thickness in the aluminium sheet band process is controlled.
Further, in the above-mentioned thickness adaptive fuzzy control method for aluminium plate band rolling mill, thickness control system of the rolling mill is accepted the thick difference signal from calibrator, the quantizing factor that the expert determines and the operating experience of milling train, set up the fuzzy relation between error originated from input and error rate and the pid parameter adjustment amount, then by the controlled table of fuzzy operation, the thickness error that measures and the rate of change of thickness error are carried out obfuscation, by domain relatively, get the adjustment amount of corresponding pid parameter in the control table, be superimposed upon on the pid control parameter, hydraulic system by milling train obtains needed roll folding degree, thereby realizes adjustment and control to milling train thickness.
Further, in the above-mentioned thickness adaptive fuzzy control method for aluminium plate band rolling mill, fuzzy control process adopts the dual input of a two dimension, the Fuzzy control system of three outputs, two input variables are that thick poor e and thick difference change ec, and three output variables are three parameter K p, Ki and the Kd of PID controller regulated quantity.
Again further, in the above-mentioned thickness adaptive fuzzy control method for aluminium plate band rolling mill, described fuzzy control process carries out after having eliminated the roller influence factor, that is: under different rolling modes, after the changing value that detects bending roller force, adopt the corresponding penalty coefficient amount of being compensated, in the control corresponding that is added to the then amount, offset roller and change caused rolling condition variation.
Substantive distinguishing features and marked improvement that the present invention gives prominence to are mainly reflected in:
(1) uses fuzzy control and realize the pid parameter self adaptation, reduced band deviation end to end, improved system response time;
(2) increase the bending roller force compensate function, reduce the influence that the roller disturbance brings the product precision;
(3) increase the Process Control System software interface, improved the default precision;
(4),, cooperate software can realize the thickness High-speed Control by selecting suitable hardware and hardware configuration scheme based on this technical scheme;
(5) can improve the automaticity of milling train " thickness control system ", the rate of reducing the number of rejects and seconds is boosted productivity, and the installation level of milling train is greatly improved.
Description of drawings
By the detailed description of reference accompanying drawing to the preferred embodiments of the present invention, it is clearer that above-mentioned purpose of the present invention and advantage will become.Wherein: Fig. 1 is the control system structural representation; Fig. 2 is control principle figure; Fig. 3 is the membership function oscillogram; Fig. 4 is a flow chart.
Among Fig. 1,1 is the oil pressure measurement mechanism, and 2 is position-measurement device, and 3 is measurer for thickness, and 4 is roll, and 5 is signal processing circuit, and 6 is built-in PC, and 7 is dc drive control system.
The specific embodiment
Fuzzy control is based on the control law of knowledge rule even semantic description, and it is relatively easy to method for designing for gamma controller has proposed one, and is especially when controlled device contains the processing of the very difficult usefulness of uncertainty conventional non-linear control theory, effective especially.The present invention introduces the fuzzy control means on the basis of traditional PID control method, thereby forms complete, the feasible thickness adaptive fuzzy control method for aluminium plate band rolling mill of a cover, has obtained satisfied effect.
Fig. 1 is an aluminium plate band rolling mill thickness control system structural representation: in the aluminium sheet band operation of rolling, milling train enters the operation of rolling through 6 (built-in PCs) and 7 (dc drive control systems) control, this moment, thickness control system received measurer for thickness 3 detected thick difference signals, the controlled signal of gage controller in system (combine form by fuzzy controller and conventional PID controllers), go control valve to drive oil cylinder, and then carry out rolling processing by 4 pairs of aluminium sheet bands of roll.Wherein, the oil cylinder feedback signal is obtained by 1 oil pressure measurement mechanism and 2 position-measurement devices.
Fig. 2 is the control principle figure that aluminium plate band rolling mill thickness control system Position Control link adopts fuzzy control, be designed to the dual input of a two dimension, the Fuzzy control system of three outputs, the input language variable is that thick poor e and thick difference change ec, and output variable is three parameter K p, Ki and the Kd of PID controller regulated quantity.Each thick poor e and thick difference constantly changes ec, the actual (real) thickness h and the thickness value h given in advance that monitor by calibrator
REFCompare and obtain.
For above linguistic variable, its excursion is basic domain.As for cold rolled sheet, the excursion that thick poor e and thick difference change ec be ± 50um, and the excursion of adjusting parameter P is ± 0.3, and the excursion of I is ± 0.06mm that the excursion of D is ± 3mm to quantize basic domain according to quantizing factor ke and kec then:
E＝＞X＝{-6，-5，-4，-3，-2，-1，0，1，2，3，4，5，6}；
EC＝＞Y＝{-6，-5，-4，-3，-2，-1，0，1，2，3，4，5，6}；
P＝＞Z1＝{-6，-5，-4，-3，-2，-1，0，1，2，3，4，5，6}；
I＝＞Z2＝{-6，-5，-4，-3，-2，-1，0，1，2，3，4，5，6}；
D＝＞Z3＝{-6，-5，-4，-3，-2，-1，0，1，2，3，4，5，6}。
After determining to quantize domain,, determine that the pairing language value of deviation e number is 8, that is: to each linguistic variable ambiguity in definition subclass
X={Ai} (i=1 ... 8)=PB, PM, PS, PO, NO, NS, NM, NB}, the pairing linguistic variable of rate of change ec of deviation is 7, that is:
Y={Bj} (j=1....7)=and PB, PM, PS, 0, NS, NM, NB}, linguistic variable Z1, the Z2 of bias adjustment parameter P, I, D correspondence, Z3 are divided into 7 usually:
Z1＝{Ck1}(k1＝1....7)＝{PB，PM，PS，0，NS，NM，NB}，
Z2＝{Ck2}(k2＝1....7)＝{PB，PM，PS，0，NS，NM，NB}，
Z3＝{Ck3}(k3＝1....7)＝{PB，PM，PS，0，NS，NM，NB}。
Determine that the membership function oscillogram is the trigonometric function waveform, as shown in Figure 3, determine that according to each fuzzy subset the membership function that quantizes each element in the domain obtains the membership function table, sees Table 1 again.
Fuzzy relation is determined according to operating experience.Might as well set fuzzy control rule is:
IF Ai AND Bj THEN Ck, such as: A=PM and B=PS, then Z=NB.
Its fuzzy relation is: R1=Ui, j (Ai*Bj*C1ij); R2=Ui, j (Ai*Bj*C2ij); R3=Ui, j (Ai*Bj*C3ij).That is:
μR1(x，y，z1)＝∨i，j(μAi(x)∧μBj(y)∧μCij(z1))
μR2(x，y，z2)＝∨i，j(μAi(x)∧μBj(y)∧μCij(z2))
μR3(x，y，z3)＝∨i，j(μAi(x)∧μBj(y)∧μCij(z3))
Table 1: membership function control law table
Can obtain fuzzy control rule table thus.Carry out fuzzy judgment then, be about to the fuzzy quantity sharpening of three parameters, adopt comparatively simple maximum membership degree judgement method, by fuzzy subset C1ij; , when C2ij, C3ij determine output, when there being z1
*, z2
*, z3
*, and: μ C1ij (z1
*) 〉=μ C1ij (z1), μ C2ij (z2
*) 〉=μ C2ij (z2), μ C3ij (z3
*) 〉=μ C1ij (z3) then gets μ 1
*=z1
*, μ 2
*=z2
*, μ 3
*=z3
*Adjacent multiple spot is arranged simultaneously when the maximum, then μ
*Get the mean value of these points.Calculate the fuzzy output question blank of pid parameter by these, as shown in table 2.
Table 2: control law table
Like this, the control method that adopts fuzzy control and traditional PI D to combine, set up fuzzy relation between error originated from input and error rate and the pid parameter adjustment amount according to the milling train operating experience, then by the controlled table of fuzzy operation, the thickness error that measures and the rate of change of thickness error are carried out obfuscation, by domain relatively, get the adjustment amount of corresponding pid parameter in the control table, be superimposed upon on the pid control parameter, hydraulic system by milling train just can obtain needed roll folding degree, thereby processing obtains meeting the aluminium foil band that THICKNESS CONTROL requires.
Use such scheme and programme, be input to then in the middle of the built-in PC, just can realize the Intellectualized monitoring (AGC) of aluminium strip rolling mill thickness.Fig. 4 has provided the flow chart of establishment control software: when making software, at first formulate needed quantizing factor in the fuzzy controller, the membership function table, the fuzzy subset, fuzzy control rule and scale factor, adopt gravity model appoach as fuzzy synthetic method of the present invention, synthesize fuzzy polling list according to gravity model appoach, system obtains thick poor, after obtaining thick poor variable quantity, calculate the affiliated domain of thick difference and thick poor variable quantity, calculate the affiliated fuzzy subset's scope of this thick difference in view of the above, thereby determine its address in fuzzy polling list, get this address contents and just can get fuzzy control quantity, be superimposed in the PID controlled quentity controlled variable after being multiplied by scale factor, The whole control is just promptly finished.
In the process, making roller is that diastrophic bending roller force can cause external disturbance to milling train thickness control system, when this interference mainly is divided into position ring during to the influence of roll gap and pressure rings to the influence of pressure.Under different rolling modes, behind the changing value that detects bending roller force, need to adopt different penalty coefficients, the amount of being compensated in the control corresponding that is added to the then amount, is offset roller and is changed caused rolling condition variation.
In a word, technical solution of the present invention gathers expert and operating personnel's the field experience of enriching to form the thickness fuzzy control rule table, replaces the commissioning staff personal experience, can realize the PID gain-adaptive, suppresses end to end more overproof of band well.Wherein fuzzy control part can be formulated fuzzy output control question blank by off-line, reduces software operation time.Practical application shows that this method has good control effect for the processing of aluminium strip aluminium foil, and the function of milling train " thickness control system " will be more perfect afterwards to use this technical scheme, trend towards full automation more, can improve the installation level of milling train greatly.
Need to prove that at last except that above-mentioned embodiment, the present invention still has other numerous embodiments.All employings are equal to the technical scheme of replacement or equivalent transformation formation, all drop within the scope of protection of present invention.
Claims (4)
1. thickness adaptive fuzzy control method for aluminium plate band rolling mill is characterized in that: the control method that adopts fuzzy control and traditional PI D to combine, the milling train thickness in the aluminium sheet band process is controlled.
2. thickness adaptive fuzzy control method for aluminium plate band rolling mill according to claim 1, it is characterized in that: thickness control system of the rolling mill is accepted the thick difference signal from calibrator, the quantizing factor that the expert determines and the operating experience of milling train, set up the fuzzy relation between error originated from input and error rate and the pid parameter adjustment amount, then by the controlled table of fuzzy operation, the thickness error that measures and the rate of change of thickness error are carried out obfuscation, by domain relatively, get the adjustment amount of corresponding pid parameter in the control table, be superimposed upon on the pid control parameter, hydraulic system by milling train obtains needed roll folding degree, thereby realizes adjustment and control to milling train thickness.
3. thickness adaptive fuzzy control method for aluminium plate band rolling mill according to claim 2, it is characterized in that: fuzzy control process adopts the dual input of a two dimension, the Fuzzy control system of three outputs, two input variables are that thick poor e and thick difference change ec, and three output variables are three parameter K p, Ki and the Kd of PID controller regulated quantity.
4. according to claim 1 or 2 or 3 described thickness adaptive fuzzy control method for aluminium plate band rolling mill, it is characterized in that: described fuzzy control process carries out after having eliminated the roller influence factor, promptly, under different rolling modes, after the changing value that detects bending roller force, adopt the corresponding penalty coefficient amount of being compensated, in the control corresponding that is added to the then amount, offset roller and change caused rolling condition variation.
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| CN101224470B (en) * | 2008-01-18 | 2010-06-23 | 西南铝业（集团）有限责任公司 | Plate producing thickness controlling method |
| CN101693257B (en) * | 2009-09-30 | 2011-10-19 | 唐山国丰钢铁有限公司 | Method for realizing continuous feedback control by duality of hot finishing outlet instruments |
| CN102271832A (en) * | 2008-12-05 | 2011-12-07 | 西门子Vai金属科技有限责任公司 | Method and device for the semi-active reduction of pressure oscillations in a hydraulic system |
| CN102284505A (en) * | 2011-08-25 | 2011-12-21 | 东华大学 | System for controlling thickness of fuzzy PI (Proportional Integral) based on ARM (Advanced RISC machines) |
| CN102328009A (en) * | 2011-09-30 | 2012-01-25 | 佛山市顺德工业与信息技术研究中心有限公司 | Fuzzy control fuzzification and fuzzy reasoning method for non-linear precise forging press |
| CN101661294B (en) * | 2009-09-03 | 2012-06-13 | 苏州有色金属研究院有限公司 | Self-adaptive fuzzy control method of strip centering system |
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| CN102271832A (en) * | 2008-12-05 | 2011-12-07 | 西门子Vai金属科技有限责任公司 | Method and device for the semi-active reduction of pressure oscillations in a hydraulic system |
| CN101661294B (en) * | 2009-09-03 | 2012-06-13 | 苏州有色金属研究院有限公司 | Self-adaptive fuzzy control method of strip centering system |
| CN101693257B (en) * | 2009-09-30 | 2011-10-19 | 唐山国丰钢铁有限公司 | Method for realizing continuous feedback control by duality of hot finishing outlet instruments |
| CN102284505A (en) * | 2011-08-25 | 2011-12-21 | 东华大学 | System for controlling thickness of fuzzy PI (Proportional Integral) based on ARM (Advanced RISC machines) |
| CN102328009A (en) * | 2011-09-30 | 2012-01-25 | 佛山市顺德工业与信息技术研究中心有限公司 | Fuzzy control fuzzification and fuzzy reasoning method for non-linear precise forging press |
| CN102328009B (en) * | 2011-09-30 | 2013-09-11 | 佛山市顺德工业与信息技术研究中心有限公司 | Fuzzy control fuzzification and fuzzy reasoning method for non-linear precise forging press |
| CN104841699B (en) * | 2014-02-14 | 2017-01-18 | 宝山钢铁股份有限公司 | Hot continuous rolling thickness AGC method having gain segmentation control |
| CN104841699A (en) * | 2014-02-14 | 2015-08-19 | 宝山钢铁股份有限公司 | Hot continuous rolling thickness AGC method having gain segmentation control |
| CN110314938A (en) * | 2018-03-29 | 2019-10-11 | 上海梅山钢铁股份有限公司 | The milling method that thickens of hot strip rolling mm finishing mill unit |
| CN110314938B (en) * | 2018-03-29 | 2020-07-21 | 上海梅山钢铁股份有限公司 | Thickening rolling method of hot continuous rolling finishing mill set for strip steel |
| CN109647901A (en) * | 2018-12-28 | 2019-04-19 | 中冶南方工程技术有限公司 | A kind of cold-rolling mill feedforward method for controlling thickness and device based on fuzzy control |
| CN109877164A (en) * | 2018-12-28 | 2019-06-14 | 中冶南方工程技术有限公司 | A kind of cold-rolling mill second flow method for controlling thickness and device based on fuzzy control |
| CN109647901B (en) * | 2018-12-28 | 2024-01-26 | 中冶南方工程技术有限公司 | Cold rolling mill feedforward thickness control method and device based on fuzzy control |
| CN109877164B (en) * | 2018-12-28 | 2024-03-22 | 中冶南方工程技术有限公司 | Second flow thickness control method and device for cold rolling mill based on fuzzy control |
| CN116713314A (en) * | 2023-07-12 | 2023-09-08 | 索罗曼(广州)新材料有限公司 | Titanium flat bar rolling one-step forming device and method |
| CN116713314B (en) * | 2023-07-12 | 2024-01-23 | 索罗曼(广州)新材料有限公司 | Titanium flat bar rolling one-step forming device and method |
| CN116603869A (en) * | 2023-07-20 | 2023-08-18 | 江苏甬金金属科技有限公司 | Deviation correction control method and system based on feedback optimization |
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