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Real-Time Nonlinear Model Predictive Control of a Glass Forming Process Using a Finite Element Model

机译:使用有限元模型的玻璃成型过程实时非线性模型预测控制

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The control of complex forming processes (e.g., glass forming processes) is a challenging topic due to the mostly strongly nonlinear behavior and the spatially distributed nature of the process. In this paper a new approach for the real-time control of a spatially distributed temperature profile of an industrial glass forming process is presented. As the temperature in the forming zone cannot be measured directly, it is estimated by the numerical solution of the partial differential equation for heat transfer by a finite element scheme. The numerical solution of the optimization problem is performed by the solver HQP (Huge Quadratic Programming). In order to meet real-time requirements, in each sampling interval the full finite element discretization of the temperature profile is reduced considerably by a spline approximation. Results of the NMPC concept are compared with conventional PI control results. It is shown that NMPC stabilizes the temperature of the forming zone much better than PI control. The proposed NMPC scheme is robust against model mismatch of the disturbance model. Furthermore, the allowed parameter settings for a real-time application (i.e., control horizon, sampling period) have been determined. The approach can easily be adapted to other forming processes where the temperature profile shall be controlled.
机译:复杂的成形过程(例如,玻璃成形过程)的控制是一个具有挑战性的主题,因为该过程主要具有强烈的非线性行为和该过程的空间分布特性。本文提出了一种实时控制工业玻璃成型过程中空间分布温度曲线的新方法。由于不能直接测量成形区域中的温度,因此通过有限元方案通过传热的偏微分方程的数值解进行估算。优化问题的数值解决方案由求解器HQP(巨大二次规划)执行。为了满足实时要求,在每个采样间隔中,通过样条曲线逼近大大降低了温度曲线的全部有限元离散化。将NMPC概念的结果与常规PI控制结果进行比较。结果表明,与PI控制相比,NMPC能更好地稳定成形区的温度。所提出的NMPC方案对于干扰模型的模型失配是鲁棒的。此外,已经确定了用于实时应用的允许参数设置(即,控制范围,采样周期)。该方法可以很容易地适应应控制温度曲线的其他成型工艺。

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