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首页> 外文会议>2009年中国控制与决策会议（2009 Chinese Control and Decision Conference）论文集 >Batch Process Control from Practice to 2D Model Predictive Control
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Batch Process Control from Practice to 2D Model Predictive Control

机译：从实践到2D模型预测控制的批处理控制

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Owing to the natures of batch processes, such as high nonlinearity, time-varying, and limited batch time duration, their control remains as a challenge to modern industries. This paper takes a typical batch process, injection molding, as an example to present a set of control schemes for batch processes. Advanced control algorithms such as adaptive control and model predictive control have been adopted to deal with the inherent process nonlinear and time-varying characteristics. These control algorithms are all focused on single cycle control performance. A multi-cycle two-dimensional model predictive learning control has been developed for batch processes control to take advantages of batch process repeatability. In this presentation, besides showing the control results/methods, the authors wish to illustrate the development evolution with their understanding of the natures of batch processes in general, injection molding in particular.
机译：由于批处理过程的特性，例如高非线性，时变和有限的批处理持续时间，其控制仍然是现代工业的挑战。本文以典型的批处理过程（注塑成型）为例，介绍了一组用于批处理过程的控制方案。已采用诸如自适应控制和模型预测控制之类的高级控制算法来处理固有的过程非线性和时变特性。这些控制算法都集中在单周期控制性能上。已经开发了用于批处理过程控制的多周期二维模型预测学习控制，以利用批处理过程的可重复性。在此演示文稿中，除了显示控制结果/方法外，作者还希望通过对批处理过程（尤其是注塑）的本质的理解来说明开发的发展。

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