An integrated system of inferential measurement and control of polymer extrusion for self-tuning optimisation and response to disturbances

挤出过程，其中聚合物颗粒被熔化并通过在加热的桶中旋转的螺杆输送，形成了几乎所有聚合物加工操作的基础。在该项目中，将通过过程建模、推理测量和更智能的过程控制方法的进步，开发一个用于改善挤出过程性能的综合框架。这将需要开发透明的在线模型，将第一原则模型与可观察的在线数据分析相结合。它将能够对关键性能指标进行推理测量;识别过程故障;在线优化设置;以及根据不断变化的进料和条件进行自我调整的能力。最终结果将是一种新的挤出控制方法，这将为准确，高效和灵活的挤出加工提供一个全面的框架。这种装置将对实现更高的产品质量和更大的回收进料潜力产生重大影响，同时减少停机时间，能源消耗和宝贵的聚烯烃资源的浪费。为了开发这一系统，需要在许多领域进行关键研究。这些包括新的理论（开发新的建模技术;对进料变化的鲁棒在线系统识别）;创新的实际测量（高频信号的真实的实时数据采集和处理）和用于解释复杂数据的创新数据分析（数据与非均匀熔化的相关性、材料降解的识别、鲁棒的自适应控制策略的集成）。这项研究中技术的发展也将为在新兴的复杂加工应用中取得更大的成功提供一个理想的平台，例如反应挤出，微挤出和纳米复合材料的复合。

The process of extrusion, whereby polymer granules are melted and conveyed by a screw rotating in a heated barrel, forms the basis of practically all polymer processing operations. In this project an integrated framework for improved performance of extrusion processes will be developed through advances in process modelling, inferential measurement and a more intelligent approach to control of the process. This will require the development of transparent on-line models integrating first-principles' models with analysis of observable on-line data. It will enable inferential measurement of key performance indicators; identification of process faults; on-line optimisation of settings; and an ability to self-tune to changing feed materials and conditions. The end result will be a novel methodology for extrusion control which will provide a comprehensive framework for accurate, efficient and flexible extrusion processing. Such a device would have a major impact on achieving higher product quality and greater potential of recycled feed material while reducing downtime, energy consumption and wastage of valuable polyolefin resources. In order to develop this system, pivotal research is required in a number of areas. These include new theory (development of novel modelling techniques; robust on-line system identification for feed material changes); innovative practical measurements (real time data acquisition and processing of high frequency signals) and innovative data analysis for interpretation of complex data (correlation of data with non-homogenous melting, identification of material degradation, integration in a robust, adaptive control strategy). The development of techniques in this research will also provide an ideal platform for achieving greater success in emerging complex processing applications, for example in reactive extrusion, micro-extrusion and compounding of nanocomposites.