Study On Predictive Control And Optimization Simulation For The Rolling Force Of Cold Mill

With the economic and social development, cold strip steel in the proportion of the total steel consumption continues to increase, and is playing an increasingly important role. So the quality requirements of cold strip steel are higher and higher, the production requirements become bigger and bigger, and has put forward a higher request to the production of cold strip steel. Rolling force control of hydraulic technology is indispensable to the process of the cold strip steel production. The performance of the rolling force control will directly affect the quality of steel products. Therefore, there is an important theoretical and practical significance for the study to the hydraulic control system for the cold rolling force.This paper describes the mechanical structure of the cold rolling mill and the hydraulic force control system. Through the research and learning to the cold rolling force of the hydraulic control system and the characteristics of the process, we get a rolling force control system hydraulic mathematical model, and provide a practical background and theoretical basis for the cold rolling force control.Considering the rolling force of the hydraulic control system, we introduce generalized predictive control algorithm to control the rolling force. The algorithm based on CARIMA model, using a long time optimization performance, combined with recognition and self-correction mechanism and has strong robustness and model requires low. This paper proposed an inhibition overshoot improvement strategy for the generalized predictive control algorithm and get a better control effect. On this basis, proposed the design of rolling force of the hydraulic unconstrained generalized predictive control with the mathematical model.On the actual conditions, there exist a lot of constraints. it cannot be directly to get the optimal control input from the analytical method. This paper introduced the differential evolution algorithm to the rolling optimization stage of generalized predictive control, change the constraints generalized predictive control performance optimization problem into the minimum differential evolution algorithm constrained optimization problem, and finally get the amount of optimal control that meet the constraints through the iterative calculation. Then considering the cold rolling force for the hydraulic control system, combine the constraints, using differential evolution algorithm for generalized predictive control to achieve the control of rolling force.