卷对卷制程加速阶段的增量模型预测控制

Incremental Model Predictive Control during the Speed-up Phase in Roll-to-roll Process

  • 摘要: 针对卷对卷制程(roll-to-roll,R2R)在印刷生产中从低速到高速的加速过程,存在印刷网布张力波动引起套印误差的问题,提出一种增量模型预测控制(model predictive control, MPC)方法,提高印刷精度以减少在加速过程中产生的废料。通过分析稳速阶段数学模型以及加速阶段系统特性,将加速引起的套印误差视为系统外部扰动,建立加速阶段数学模型,结合实时测量值当中蕴含的扰动量变化信息,提出了增量模型预测控制方法。实验分析表明,相较于已发表的完全解耦比例微分(fully decoupled proportional-derivative,FDPD)和基于扰动观测器的比例微分(disturbance observer-based compensation proportional-derivative, DOCPD)控制方法,MPC具有控制效果和性能上的优势。

     

    Abstract: To address the register errors caused by tension fluctuations in roll-to-roll (R2R) printing during acceleration from low to high speeds, this study proposes an incremental model predictive control (MPC) method to improve printing accuracy and reduce material waste during acceleration. By analyzing the mathematical model during steady-speed phases and the system characteristics during acceleration phases, the register errors induced by acceleration are treated as external disturbances. A mathematical model for the acceleration phase is established, integrating real-time measurement data that reflects disturbance variations. The proposed incremental MPC method leverages this model to enhance control performance. Experimental results demonstrate that compared to existing methods such as fully decoupled proportional-derivative (FDPD) control and disturbance observer-based compensation proportional-derivative (DOCPD) control, the MPC approach exhibits advantages in control effectiveness and performance.

     

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