Flatness Control Based on Dynamic Effective Matrix for Cold Strip Mills

Steel strips are the main of steel products and flatness is an important quality indicator of steel strips. Flatness control is the key and highly difficult technique of strip mills. The bottle-neck restricting the improvement of flatness control techniques is that the research on flatness theories and control mathematic models is not in accordance with the requirement of technique developments. To build a simple, rapid and accurate explicit formulation control model has become an urgent need for the development of flatness control technique. This paper puts forward the conception of dynamic effective matrix based on the effective matrix method for flatness control proposed by the authors under the consideration of the influence of the change of parameters in roiling processes on the effective matrix, and the concept is validated by industrial productions. Three methods of the effective matrix generation are induced： the calculation method based on the flatness prediction model; the calculation method based on the data excavation in rolling processes and the direct calculation method based on the network model. A fuzzy neural network effective matrix model is built based on the clusters, and then the network structure is optimized and the high-speed-calculation problem of the dynamic effective matrix is solved. The flatness control scheme for cold strip mills is proposed based on the dynamic effective matrix. On stand 5 of the 1 220 mm five-stand 4-high cold strip tandem mill, the industrial experiment with the control methods of tilting roll and bending roll is done by the control scheme of the static effective matrix and the dynamic effective matrix, respectively. The experiment result proves that the control effect of the dynamic effective matrix is much better than that of the static effective matrix. This paper proposes a new idea and method for the dynamic flatness control in the rolling processes of cold strip mills and develops the theory and model of the flatness control effective matrix method.

VCR and ASR technology for profile and flatness control in hot strip mills

The roll contour pattern and variety of work and backup rolls in service and its effect on profile and flatness control performance in 1 700 mm hot strip mill at Wuhan Iron and Steel(Group) Corporation were tested and analyzed by the developed finite element models of different typical roll contours configurations.A rather smooth local work roll contour near strip edges and an increase in rolled length can be obtained by application of long stroke work roll shifting system with conventional work roll contours that is incapable of the crown control.In comparison with the conventional backup and work roll contours configuration,the crown control range by the roll bending force enhances by 12.79% and the roll gap stiffness increases by 25.26% with the developed asymmetry self-compensating work rolls(ASR) and varying contact backup rolls(VCR).A better strip profile and flatness quality,an increase in coil numbers within the rolling campaign and a significant alleviated effect of severe work roll wear contours on performance of edge drop control are achieved by the application of ASR with crown control and wear control ability in downstream stand F5 and VCR in all stands of 1 700 mm hot strip mill.

Development and application of cold strip rolling flatness control system in Ansteel

In this paper,the flatness control technology AnShaper^(TM) for cold-rolling mill and industry application are introduced.AnShaper^(TM) includes;partitioning piezomagnetic shape meter for flatness measurement for cold-rolling strip;flatness measured signals processing system based on digital signal processing(DSP);flatness feedback control model system based on the control efficiency of flatness control actuators and model adaptive function.The application verifies that strip flatness can meet the need of high quality product by using AnShaperTM.The average flatness quality is about 5Ⅰ-unit and the 0.18 mm ultrathin thickness strip flatness is 10Ⅰ-unit.

Theory-Intelligent Dynamic Matrix Model of Flatness Control for Cold Rolled Strips

In order to increase the precision of flatness control, considering the principle and the measured data of rolling process essence, the theory-intelligent dynamic matrix model of flatness control is established by using theory and in-telligent methods synthetically. The network model for rapidly calculating the theory effective matrix is established by the BP network optimized by the particle swarm algorithm. The network model for rapidly calculating the meas- urement effective matrix is established by the RBF network optimized by the cluster algorithm. The flatness control model can track the practical situation of roiling process by on-line selVlearning. The scheme for flatness control quantity calculation is established by combining the theory control matrix and the measurement control matrix. The simulation result indicates that the establishment of theory-intelligent dynamic matrix model of flatness control with stable control process and high precision supplies a new way and method for studying flatness on-line control model.

Actuator Efficiency Adaptive Flatness Control Model and Its Application in 1250 mm Reversible Cold Strip Mill

The existing research of the flatness control for strip cold rolling mainly focuses on the calculation of the optimum adjustment of individual flatness actuator in accordance with the flatness deviation , which is used for general flatness control.As the basis of flatness control system , the efficiencies of flatness actuators provide a quantitative description to the law of flatness control.Therefore , the determination of actuator efficiency factors is crucial in flatness control.The strategies of closed loop feedback flatness control and rolling force feed-forward control were established respectively based on actuator efficiency factors.For the purpose of obtaining accurate efficiency factors matrixes of flatness actuators , a self-learning model of actuator efficiency factors was established.The precision of actuator efficiency factors can be improved continuously by the input of correlative measured flatness data.Meanwhile , the self-learning model of actuator efficiency factors permits the application of this flatness control for all possible types of actuators and every stand type.The application results show that the self-learning model is capable of obtaining good flatness.

Cloud Neural Fuzzy PID Hybrid Integrated Algorithm of Flatness Control

In connection with the characteristics of multi-disturbance and nonlinearity of a system for flatness control in cold rolling process, a new intelligent PID control algorithm was proposed based on a cloud model, neural network and fuzzy integration. By indeterminacy artificial intelligence, the problem of fixing the membership functions of input variables and fuzzy rules was solved in an actual fuzzy system and the nonlinear mapping between variables was implemented by neural network. The algorithm has the adaptive learning ability of neural network and the indetermi- nacy of a cloud model in processing knowledge, which makes the fuzzy system have more persuasion in the process of knowledge inference, realizing the online adaptive regulation of PID parameters and avoiding the defects of the traditional PID controller. Simulation results show that the algorithm is simple, fast and robust with good control performance and application value.

Theoretical and numerical research on effect of tension mechanisms in strip flatness electromagnetic control rolling mills

To achieve stable rolling,the influence of a tension mechanism of a large diameter ratio roll system on the rolling process of a strip flatness electromagnetic control rolling mill is studied.Through the analysis of the rolling deformation zone,the deformation zone composition form of a large diameter ratio roll system and a calculation formula of neutral angle under tension are proposed.To analyze the effect of front and post tensions on the rolling characteristic and the strip flatness control characteristic,a three-dimensional rolling finite element(FE)model of a large diameter ratio roll system with the function of roll profile electromagnetic control is established by FE software and verified by a strip flatness electromagnetic control rolling mill.Based on the model,the strip thickness characteristic,metal transverse flow,strip flatness state,and adjustment range of the loaded roll gap are analyzed for different front and post tensions setting values.The results show that changing the front or post tension setting values can improve the single-pass reduction rate of a large diameter ratio roll system and have little effect on the flatness control ability of the strip flatness electromagnetic control rolling mill.

Research and Application of Non-symmetrical Roll Bending Control of Cold Rolling Mill

The existing research of the flatness control for strip cold rolling mainly focuses on the calculation of the optimum adjustment of individual flatness actuator in accordance with the flatness deviation, which can be used for general flatness control. However, it does not work for some special rolling processes, such as the elimination of ultra single side edge-waves and the prevention of strip break due to tilting roll control overshooting. For the purpose of solving these problems, the influences of non-symmetrical work roll bending and intermediate roll bending on flatness control were analyzed by studying efficiencies of them. Moreover, impacts of two kinds of non-symmetrical roll bending control on the pressure distribution between rolls were studied theoretically. A non-symmetrical work roll bending model was developed by theoretical analysis in accordance with practical conditions. The model was applied to the revamp of a 1250 6-H reversible universal crown mill (UCM) cold mill. Theoretical study and practical applications show that the coordination utilization of the non-symmetrical work roll bending control and tilting roll control was effective in flatness control when there appeared bad strip single side edge waves, especially when the incoming strip was with a wedge shape. In addition, the risk of strip break due to tilting control overshooting could be reduced. Furthermore, the non-symmetrical roll bending control can reduce the extent of uneven distribution of pressure between rolls caused by intermediate roll shifting in flatness control and slow down roll wear. The non-symmetrical roll bending control technology has important theoretical and practical significance to better flatness control.

Intelligent control over chaos in the rolling process and its comparison with tracking control

Some existing methods for chaos control in engineering fields are analyzed and their drawbacks are pointed out. A tracking method can solve these problems to some extent, but it still depends on the mathematical model of the system to be controlled. An intelligent method based on fuzzy neural network (FNN) is used to control chaos in engineering fields. The FNN is employed to learn the inherent dynamics from the input and output of chaos, which can be used in the inverse system method, so that the method is free of the exact mathematical model of the system to be controlled. This intelligent method is compared with tracking method in the presence of measurement noise and model error. Simulation results show its superiority and feasibility.

Backup roll contour in finishing trains of hot rolling based on hybrid genetic algorithm

On the basis of integrating two-dimensional varying thickness finite elementmethod with hybrid genetic algorithm, a precise model was developed to design ideal backup rollcontour (Varying Contact Backup Roll, in short VCR) in finishing rains of hot rolling rapidly andefficaciously. Additionally, a lot of good actual effects of VCR, such as evident improvement ofprofile and flatness of strip, remarkable decrease of roll consume, excellent maneuverability andmaintenance, and so on, were validated by long-term industrial tests in hot rolling strip plant ofWuhan Iron and Steel Group Corporation (WISCO).

Analysis of Stability and Large Deflection Buckle of Rolled Strip by Third Power B-Spline Function Method

A new method——the third power B-spline function method is developed to analyse the stability and the buckle of rolled strip under residual stress.The large deflection theory of thin plate is used to calculate the buckle of rolled strip and criterion of critical buckle is given.The computed results tally with those of experiment well,which provides theoretical basis and method for developing the mathematical model of flatness control.

Improvement in shape control performance of finishing mills in endless rolling production line

Donghua steel continuous casting-rolling(DSCCR)production line is an endless rolling production line independently integrated and developed by a Chinese enterprise.To solve the problem of out-of-control shape caused by insufficient adjustment ability of work roll bending force of DSCCR finishing mills,the backup roll contours of the finishing mill were optimized considering multi-objectives,and varying contact length backup roll(VCR)contours matching the concave work rolls were designed based on the rapid rolls-strip deformation calculation model,which integrated the elastic deformation of the rolls and the fast plastic deformation of the rolled strip.The simulation results showed that VCR configuration can significantly enhance the control efficiency of the work roll bending force and increase the transverse stiffness of rolling mill compared with the conventional roll configuration.In addition,VCR backup roll can improve the contact state between backup roll and work roll.The industrial production showed that the bending force setup value was more reasonable and the strip crown control accuracy was improved.

Data-based flatness prediction and optimization in tandem cold rolling

In cold rolling process,the flatness actuator efficiency is the basis of the flatness control system.The precision of flatness is determined by the setpoints of flatness actuators.In the presence of modeling uncertainties and unmodeled nonlinearities in rolling process,it is difficult to obtain efficiency factors and setpoints of flatness actuators accurately.Based on the production data,a method to obtain the flatness actuator efficiency by using partial least square(PLS)combined with orthogonal signal correction(OSC)was adopted.Compared with the experiential method and principal component analysis method,the OSC-PLS method shows superior performance in obtaining the flatness actuator efficiency factors at the last stand.Furthermore,kernel partial least square combined with artificial neural network(KPLS-ANN)was proposed to predict the flatness values and optimize the setpoints of flatness actuators.Compared with KPLS or ANN,KPLS-ANN shows the best predictive ability.The root mean square error,mean absolute error and mean absolute percentage error are 0.51 IU,0.34 IU and 0.09,respectively.After the setpoints of flatness actuators are optimized,KPLS-ANN shows better optimization ability.The result in an average flatness standard deviation is 2.22 IU,while the unoptimized value is 4.10 IU.

Roll Subsectional Cooling Adaptive Fuzzy Control Based on Fuzzy Model Inversion

Flatness is an important equality indicator of strip rolling and roll subsectional cooling is an important method for flatness control, especially for high order flatness component control. It is very hard to build the mathematic model of roll subsectional cooling because of its characteristics of nonlinearity, hysteresis quality and strong coupling, etc. In order to improve the control effect of roll subsectional cooling control model, the roll subsectional cooling adaptive fuzzy control model based on fuzzy model inversion is built according to the separation principle of fuzzy form on the basis of the conventional fuzzy control model, where the parameters of the fuzzy controller can be dynamically regulated according to the change of rolling conditions. Simulation experiment results of the model indicate that the proposed roll subsectional cooling adaptive fuzzy control model based on fuzzy model inversion has high control precision and rapid response speed with strong self-learning and anti-interference capacity and a new method is provided for high precision flatness control.

An efficient energy-management strategy for a DC microgrid powered by a photovoltaic/fuel cell/battery/supercapacitor

The outcome of this paper is to suggest an efficient energy-management strategy(EMS)for a direct-current(DC)microgrid(MG).The typical MG is composed of two renewable energy sources[photovoltaic(PV)systems and fuel cells(FCs)]and two energy-storage elements(lithium-ion battery and supercapacitor).An EMS was proposed to ensure optimal bus voltage with a power-sharing arrangement between the load and the sources.As a result,in the suggested DC MG,non-linear flatness control theory was used instead of the traditional proportional-integral control approach.The suggested EMS is intended to supply high power quality to the load under varying load conditions with fluctuating solar irradiation while considering the FC status.To validate and prove the effectiveness of the proposed EMS,a MATLAB®environment was used.In addition,the output power of the PV system was maximized using the particle swarm optimization algorithm as a maximum power point tracking(MPPT)technique to track the MPP of the 3000-W PV system under different irradiance conditions.The results show that the suggested EMS delivers a stable and smooth DC bus voltage with minimum overshoot value(0.1%)and improved ripple content(0.1%).As a result,the performance of the DC MG was enhanced by employing the flatness control theory,which provides higher power quality by stabilizing the bus voltage.