The present investigation devises a flatness control strategy for a five‐stand tandem cold rolling mill. In addition, intermediate roll shifting (IRS)–induced rigidity characteristics of the six‐high Universal Crown Control mill (UCM mill) as a key model for the automatic thickness and flatness control systems are established. A three‐dimensional elastic‐plastic finite element analysis for a strip rolling process is conducted when the UCM mill is subjected to different IRS values. The convergence and precision of the simulation model are verified using experimental data in a five‐stand tandem cold rolling line. Through a steady‐state rolling analysis of the process, the vertical and transverse rigidity characteristic curves of the roll‐stack, reduction strain field of the strip, variation in strip crown, elastic deflection of the rolls, and contact stress field between rolls are extracted. The results show that the IRS obviously changes the deflection curves of the rolls and then causes the variations in the exit thickness and transverse thickness difference of the strip. The nonuniform stress distribution between rolls caused by the increasingly IRS value lead to local stress concentration on the side of the roll. A mechanism for the effect of IRS on the rigidity characteristics of the mill is presented and discussed.

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Purpose In the cold rolling process, friction coefficient, oil film thickness and other factors vary dramatically with the change in the rolling speed, which seriously affects the strip thickness deviation. This paper aims to study the law among the parameters in the rolling process to improve the strip control precision. Design/methodology/approach In this paper, a novel forecasting model of the roll gap based on support vector machine (SVM) optimized by particle swarm optimization with compression factor (CF-PSO) is proposed. Based on lots of online data, the roll gap models regressed by PSO-SVM, genetic algorithm (GA)-SVM and CF-PSO-SVM are obtained and verified through evaluating the performances with the decision coefficient (R2), mean absolute error and root mean square error. In addition, with the good forecasting performances of CF-PSO-SVM, a roll gap compensation model is studied. Findings The results indicate that the proposed CF-PSO-SVM has excellent learning regression ability compared with other optimization algorithms. And the obtained roll gap compensation model based on the rolling speed and plastic coefficient have been applied in product, which is validated and gets a good product effect. Originality/value In this paper, the SVM algorithm is combined with traditional rolling technology to solve the problems in actual production, which has great supporting significance for the improvement of production efficiency.

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Tandem cold rolling is a high-speed, high-efficiency, and complex production process. In some cases, minor interference or disoperation may result in large economic losses. To improve control performance and enhance system robustness, an optimal tension and thickness control method is presented in this paper. The control method is designed based on the receding horizon control (RHC) strategy, which has good tracking performance and strong constraint handling capability. First, a state space model is constructed to describe the tension and thickness of the tandem cold rolling process. Then, according to the system model, a RHC controller is designed and introduced into the control system. Based on field data, model verification and a series of experiments are completed. The results show that the proposed RHC control strategy can effectively reduce the effects of disturbances and has excellent control performance compared with the conventional proportion and integration (PI) control strategy.