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Model Predictive Control with Linear Programming for the Strip Infeed in Hot Rolling Mills

机译:热轧轧机中带材进料线性规划模型预测控制

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A model-based predictive approach is proposed for the strip head motion control during the steel strip infeed in hot rolling finishing mills. The design is based on a nonlinear simplified mathematical model in a form of ordinary differential equations. It is already shown that this model captures the behavior of FEM models for the strip and the roll gap in an excellent manner. Then the simplified time variant linear model is considered and the discrete-time model is derived in a straightforward manner. In addition the property of flatness is exploited to derive an efficient formulation for the optimization problems. We develop an optimal controller based on a linear programming and compare it with standard quadratic programming. It is shown that the proposed linear program is both more efficient than the quadratic program and the performance is equivalent. Therefore, the linear approach is convenient for the real-time application even without high performance computers. The proposed controller is tested in a co-simulation environment using FEM element model for the strip integrated in HOTINT together with a highly nonlinear roll gap model. The simulation results show the excellent accordance of the controlled infeed process for both models (ODE and FEM), as well as the high performance of the closed loop.
机译:在热轧精加工厂的钢带进料期间提出了一种基于模型的预测方法。该设计基于普通微分方程形式的非线性简化的数学模型。已经表明,这种模型以优异的方式捕获条带和滚动间隙的FEM模型的行为。然后考虑简化的时间变型线性模型,并且以直接的方式导出离散时间模型。此外,利用平坦度的性质来得出有效的优化问题。我们基于线性编程开发了最佳控制器,并将其与标准二次编程进行比较。结果表明,所提出的线性程序比二次程序更有效,并且性能等同。因此,即使没有高性能计算机,即使没有高性能的计算机,线性方法也是方便的实时应用。使用FEM元件模型在与高度非线性滚动间隙模型中集成的条带中集成的带材的FEM元件模型中所提出的控制器在共模仿真环境中进行测试。仿真结果表明,型号(ode和FEM)的受控进给过程以及闭环的高性能,表明了优异的。

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