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PurposeIn the process of cold rolled strip, there is tight coupling between flatness control and gauge control. The variation of the roll gap caused by the change of bending force will lead to the change of rolling force. Furthermore, it can cause a deep impact on the control accuracy of strip exit thickness and exit crown. The purpose of this paper is to improve the accuracy of the bending force preset value for cold rolled strip.Design/methodology/approachIn this paper, the bending force preset control strategy with considering of rolling force was proposed for the first time and the preset objective function of bending force was established on the basis of the two-objective optimization of bending force and rolling force. Meanwhile, the multi-objective intelligent algorithm – INSGA-II – was used to solve the objective function.FindingsThe proposed bending force multi-objective preset model has been tested in a 1,450 mm tandem cold rolling line. The analyzed results of field data show that the deviations of strip exit thickness and exit crown are reduced effectively by using the improved model, and at the same time, more reasonable bending force preset values are obtained, which can enhance the accuracy of flatness preset control.Originality/valueA preset model of bending force with considering flatness and gauge is proposed in this paper and the multi-objective function of bending force preset is established on the basis of the two-objective optimization of bending force and rolling force. The value lies in proposing a new decoupling method of rolling force and bending force.

During the flatness control process, there are frequently some uncoordinated regulating behaviors in the flatness actuator group. This has a bad influence on the flatness control accuracy and the flatness control efficiency. Therefore, a collaboration strategy based on conflict resolution for the flatness actuator group has been proposed in this paper. First of all, the feature of flatness measurement value is extracted through establishing the actual flatness condition discriminating factor. After that, the coordination cooperation that is appropriate to the actual flatness condition is developed for the flatness actuator group. Finally, the optimal adjustment of the actuator population is solved by the coordinated algorithm of Topkis-Veinott and genetic algorithm collaborative optimization. The collaboration strategy proposed in this paper has been successfully applied to a flatness control system of a 1450 mm five-stand cold rolling mill.

Through taking the cold rolling process as the research object, the three-dimensional finite element model of the strip rolling process is established by using ANSYS/LS-DYNA software. The simulation results of the finite element model have a good fit with the actual production data. The rolling process is dynamically simulated, and the distribution curves of important rolling parameters such as equivalent stress, control efficiency coefficient, transverse rolling pressure, lateral thickness and work roll deflection is obtained. The research results of this paper have strong practicability for the process control of cold strip rolling mill. The research results have certain guiding significance for the development and optimization of the rolling control system.

Purpose The purpose of this study is to improve the global optimization ability of the Tabu search (TS) algorithm, and then improve the calculation efficiency and accuracy of rolling schedule in tandem cold rolling. Design/methodology/approach A case-based reasoning–Tabu search hybrid algorithm (CBRTS) has been presented. First, the case-based reasoning technology was adopted to obtain high-quality initial solution and then the TS algorithm was used for global optimization. Findings The optimization effect of CBRTS is compared with that of the traditional TS algorithm, and the analysis result indicates that the CBRTS has a faster convergence rate than TS, and the optimization results are closer to the global optimal. Meanwhile, the rolling schedule calculated by CBRTS is more reasonable, which can increase the production efficiency while giving full play to the capacity of equipment. Originality/value A CBRTS hybrid algorithm is presented. The strong dependence of the TS algorithm on the initial solution has been solved. The rolling schedule multi-objective optimization functions are established. The proposed algorithm is applied in a 1,450-mm tandem cold rolling production line. The improved method can reduce about half the iterations compared with the traditional one.

In cold strip rolling control system, rolling force and forward slip are the prerequisites for the model setting calculation, and the deformation resistance and friction coefficient are the main parameters that affect their predictions. A new method based on objective function is first proposed in this paper to improve the calculation accuracy of rolling force and forward slip, and the deformation resistance and friction coefficient are taken as optimisation variables. Using the multi-population co-evolutionary algorithm to solve the objective function, the required rolling force and forward slip are obtained. The pre-set values of rolling force and roller line speed are compared with the actual measured ones in a 1450 mm five-stand tandem cold mill and other researcher’s method. Results show that the calculated values are in fair agreements with the on-line measured ones, and the thickness and flatness accuracy of the final product are improved.

The setting of rolling schedule in tandem cold mill is one of the most crucial content in rolling process, which will have a direct impact on product quality and production efficiency. According to the actual requirements in the rolling process, a multi-objective function based on influence function method was built. The objective function was aimed specially at thin gauge strip and solved by Tabu search algorithm. Meanwhile, in order to avoid the strip slipping by the reduction of friction coefficient, the tension schedule was corrected according to the rolling length of work roll. The proposed optimization method has been applied successfully to a 1450mm 5-stand tandem cold mill. Application results show that the optimized rolling schedules are more close to the actual requirements and the flatness quality is improved greatly.

Under the background of industry 4.0, advanced strip control process is a central part of rolling intelligent manufacturing. In the mainstream rolling control process, the work roll bending and the intermediate roll bending are turned on at the same time. Both stepwise methods and alternative methods are conducted by sacrificing adjustment ability. In this paper, the dimension of influencing factors is increased by considering adjustment direction as constraint operator. In the rolling control process, a new intelligent assignation strategy of collaborative optimization based on artificial neural networks and Topkis–Veinott has been proposed. In AINTV collaborative optimization, the thought patterns of searching and the thought patterns of learning are combined. Five field test experiments are conducted and the flatness in different rolling stages and in different strip area is analyzed.

The process control system for tandem cold mill is the core of the production line control system. Its operating status influences the stable production of strip directly. In this paper a tandem cold rolling process control system of cold-rolled sheet plant was taken as an object, the structural framework of control system was designed, the composition and function was introduced.

The accuracy of roll force model and the rationality of roll fore adaptive model play a key role in obtaining the thickness of strip with high precision. The roll force model has been established. It includes the elastic flattened roller model and deformation resistance model considering the chemical composition of strip. A deformation resistance-based fitting curve is proposed in rolling force adaption, it can be inherited to any other thick range class. Application results show that the rolling force model and its adaptation are with high prediction accuracy and it has improved the strip thickness accuracy.

In order to improve the setting accuracy of rolling force model, a comprehensive parameters adaptive objective function of rolling force was established. During the adaptive process, the adaptive coefficients of friction coefficient and deformation resistance were taken as the optimized parameters, and the Rosenbrock algorithm was used to search the optimal solution of the objective function. The proposed adaptive method has been applied successfully to a 1450mm 5-stand tandem cold mill. Application results show that the forecast accuracy of rolling force model has been improved significantly.

In order to improve the thickness precision, the model adaption method is of great concern which is a necessary component in the thickness control system. The sample concept is first taken into the model adaption in hot tandem mill, from which the learning coefficients are updated by a series of samples. Comparing to the single sample in traditional method, the new method can consider the variance in the length direction. And the source data is more comprehensive, the robustness is increased with flexible proportion coefficients. The thickness precision in stable production process is enhanced to 35μm. On-line result shows practical value and on-line application prospect.

By the intelligent strategy of dynamic optimization in flatness target curve, the potential of the flatness control system can be completely fulfilled and the satisfying strip flatness can be speedily obtained. The traditional intervention pattern is static, open-loop, non-intelligent. In this paper, a new dynamic adjustment model of flatness target curve has been designed, by which the initial setpoint can be real-timely regulated. The closed-loop control system, equipped with the function of intelligent optimization and dynamic regulation, has been developed. A hybrid intelligent algorithm called ZOGE, in which both the searching definiteness and randomness are taken into account and the multipoint searching and single-point searching are simultaneously carried through, has been proposed. The equivalent factor of flatness target curve has been optimized by function module HYBALO, which is developed on the basis of the hybrid intelligent algorithm and is operated on CFC configuration language in SIMATIC TDC controller. The testing in the field has been conducted through a 1450 mm 5-stand tandem cold mill. The preliminary finding from the main results of testing in the field is reported: by means of the intelligent compensation model of flatness target curve, the content flatness quality of strip with thin thickness in slow rolling speed is effectively guaranteed. The maximum compensation efficiency of speed is 72.19%. The maximum compensation efficiency of thickness is 98.37%. The ability of eliminating strip flatness defect in dynamic regulation mode of flatness target curve is more powerful than the ability of eliminating strip flatness defect in conventional regulation mode.