Edge drop control of cold rolled silicon steel strip based on model predictive control

Abstract

The closed-loop edge drop control system of cold rolled silicon steel strip is a typical time-delay control system, and the measurement time-delay has a great influence on the stability of the control system. In order to improve the stability and control accuracy of the closed-loop edge drop control system, an edge drop control model based on model predictive control for cold rolled silicon steel strip is proposed in this paper. In order to improve the accuracy of control system model parameters, the priori efficiency coefficients of work roll shifting (WRS) for edge drop control are determined by rolling experiments, and the online optimization of priori efficiency coefficients is realized by process data. On this basis, the time delay analysis of control system is completed by equal flow method, and a closed-loop control strategy for edge drop control is developed by introducing predictive aging value into model predictive control. Finally, trajectory smoothing is used to complete the smooth output of predicted control, and then improve the dynamic characteristics of the closed-loop edge drop control system. Theoretical analysis, simulation experiments and application show that the model prediction-based edge drop control method has higher accuracy and faster response characteristics compared with conventional control method, and can realize high-precision edge drop control process of cold rolled silicon steel strip.