Hot Rolling Thickness Modeling and Control Method Based on Data Driven

The thickness of the rolling mill mechanism model does not gradually satisfy the current control accuracy requirements, therefore, a modeling and control method based on the data driven of strip thickness is presented.In this method, the subtractive clustering is adopted to divide the input space into several clusters.Least square support vector machine (LS-SVM) is utilized to estimate the model of the nonlinear system and forecast the output value in each cluster subset.The linear predictive control algorithm is used to implement the predictive control.The global control values are obtained by weighted strategy of the controllers.Numerical simulations show the effectiveness of the proposed method.