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As an emerging technology in the production of electrical steel, edge‐drop control (EDC) caters to the increasing requirements for the overall shape quality of strips. Herein this review, the development of EDC theory, method, and control system used in the cold‐rolling process is summarized. Also, in this review, research on EDC theory is found to be based on the 3D plastic deformation model of the strip, considering the lateral metal flow. Further, an analytical model and a numerical calculation method are employed to establish an edge‐drop calculation model with high accuracy and speed. Next, taper‐work‐roll shifting (T‐WRS), a conventional EDC technology, is found to have been greatly improved in actual production. However, T‐WRS technology involves coupling problems in terms of edge drop and crown and flatness control. Finally, the closed‐loop EDC is found to depend on the online WRS of multiple stands. Particularly, the genetic law of strip thickness in the continuous rolling process and the edge‐drop regulation characteristics of each stand in the continuous rolling mill are significant aspects; thus, a reasonable roll‐shifting control strategy must be formulated. Based on the reviewed research, the development prospect of EDC is characterized. [ABSTRACT FROM AUTHOR]

The control precision of thickness and tension is a crucial indicator for evaluating a tandem cold rolling control system. However, the control mode for field application cannot meet the actual quality requirements. Therefore, a distributed model predictive control (DMPC) strategy combined with neighborhood optimization is proposed to decrease the strip thickness deviation and tension change in this paper. First, a cold rolling model describing the relationship among the process parameters is established for the multi-stand cold rolling system. Then, according to the neighborhood optimization theory, the state evolution equation of the output system on each stand is derived. Furthermore, through proper consideration of the input and state information during optimization, optimal control variables are obtained using the proposed performance index to improve the system performance. A series of simulations were carried out with actual rolling data to analyze and validate the capability of the designed control system. The statistical data show that as roll speed disturbance occurs, the thickness and tension deviations can be controlled within respective ranges of 6 × 10 − 5 mm and 0.012 kN with the DMPC control strategy. In addition, each scan cycle calculation only takes 0.0085 s in such a strategy. Compared with the conventional control method, the thickness and tension DMPC control system provides excellent performance and can effectively enhance the strip product quality. • A state space model of thickness and tension is established with considering all the stands of cold rolling process. • A novel distributed model predictive control strategy based on Neighborhood Optimization is designed for the system. • Compared with other control strategies, the proposed DMPC strategy has excellent control performance. [ABSTRACT FROM AUTHOR]

Mill chatter is one of the most common problems in cold rolling. Thus, it is important to investigate the mill chatter phenomenon to ensure a high-speed and stable rolling process. The traditional mill chatter mechanism model cannot meet the monitoring and rapid diagnosis needs of the rolling process in the field. In this paper, a data-driven mill vibration analysis method is proposed. The main objective of this study was to develop a mill vibration monitoring method and an intelligent algorithm for mill chatter early warning. Rolling experiments showed that the proposed monitoring method could be a promising and effective technique for assessing the chatter phenomenon. The mill vibration acceleration amplitude prediction performance of a support vector regression, neural-network-based method, and extreme gradient boosting method were evaluated. The results proved that the prediction performances of the proposed extreme gradient boosting method were highly reliable with the highest determination coefficient value of 0.779, lowest mean absolute percentage error of 9.7%, and better forecast robustness under all of the dataset ratios. Meanwhile, the contribution rates of the variables on the mill vibrations were investigated, and results showed that an effective way to eliminate the mill chatter was to control the rolling speed, cumulative rolling strip length, tension and roll radius. • A mill vibration monitoring and data acquisition system is developed. • A technique to provide early warning of mill chatter based on prediction. • The SVR, NN-based, and XGBoost models are established for vibration prediction. • The results agree with the mechanistic models and physical understanding. [ABSTRACT FROM AUTHOR]

• Adjustments of flatness actuators can be determined through overall modeling. • The improved interior penalty function method is efficient for global optimization. • Optimal allocation of actuator adjustments can be achieved between sub-systems. • Double-layer optimization based control strategy can achieve optimal flatness control. The flatness control system consists of two subsystems. One is the feedback control subsystem which is used to implement the closed-loop flatness control. Another is usually referred to as feedforward control subsystem in the field of strip flatness control. To realize the cooperative control of roll bending between two subsystems, a feedforward-–feedback coordination control strategy based on double-layer optimization is proposed to obtain the optimal adjustments of actuators. Firstly, a global optimization model of actuator adjustment is established by the overall modeling, and an improved interior penalty function method is developed and utilized to solve this model subsequently. On this basis, an optimal allocation model is proposed to achieve a global optimal allocation of actuator adjustments between feedforward control and feedback control. Numerical experiments and applications show that this new control strategy and the corresponding models are effective in the flatness control process of cold rolling mill. [ABSTRACT FROM AUTHOR]

• A validated nonlinear dynamic chatter model of universal crown mill is developed. • Effect of rolling processing parameters on stand stability is given for single stand. • An improved prediction criterion for the critical rolling speed of mill chatter is proposed. • Optimal design of friction and reduction for stands No.4 and No.5 are investigated. Tandem cold rolling mills are comprehensive dynamic systems coupling with structure and rolling technology. A frequent problem is mill chatter, often occurring when rolling hard, thin materials at high speed and affecting the quality of the strip. In this paper, a dynamic increment model for chatter in a Universal Crown Control mill (UCM mill) is proposed with the considering of strip hardening, elastic deformation of the work roll, non-linear friction, transfer delay of the strip, and dynamic coupling effect of tension between adjacent stands. Mathematically, this model is based on the Taylor series expansion of the Bland-Ford-Hill rolling force equation. The comparative results of both simulation and experimental data show that this chatter model has a high accuracy. A novel, time-varying stability criterion is proposed to evaluate mill stability. Further study is provided on the optimal friction coefficient and reduction ratio required to increase the critical rolling speed and vibration stability in a tandem cold rolling mill. This mathematical criterion is validated by comparing the actual rolling speed with the calculated critical rolling speed. The present work provides a more accurate prediction of mill chatter and a basis for optimal design of rolling conditions. [ABSTRACT FROM AUTHOR]

Mill chatter is a major restriction in the high-speed rolling of high-strength and thin strips. To maintain mill stability, the friction coefficient must be kept within a certain range. Unfortunately, there is no model to calculate the lower limit of the friction. In this paper, a new model is developed to capture the minimum friction coefficient. This model is proposed based on mixed lubrication theory and monotonicity analysis in the friction curve. The verification results showed that the established model could accurately predict the minimum friction and the friction balance in tandem rolling mills. The model was utilized to design the optimal rolling conditions to expand the stability range of the friction and improve mill vibration stability. [Display omitted] • A mathematical model is proposed to predict the lower limit friction coefficient. • The model is proposed by monotonicity analysis based on mixed lubrication theory. • The model is validated to be accurate by previous literature and actual rolling test. • The optimization of the rolling condition is designed to increase mill vibration rolling stability. [ABSTRACT FROM AUTHOR]