监控控制性能和工厂模型不匹配的分层方法。

M Ziyan Sheriff, Yan-Shu Huang, Sunidhi Bachawala, Marcial Gonzelez, Zoltan K Nagy, Gintaras V Reklaitis
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引用次数: 0

摘要

控制器通常是在工厂调试期间根据固定的工艺模型进行调整的。然而,随着时间的推移,过程、过程模型和控制器都可能发生退化,因此有必要重新调整控制器或重新识别过程模型。学者们提出了多种方法来识别工厂-模型不匹配(PMM)和控制性能退化(CPD)。虽然每种方法都有其自身的优缺点,但它们一般都是针对不同的时间尺度而设计的。不同的时间尺度导致需要一种多层次的分级方法来监控、检测和管理 PMM 和 CPD,这一点可以通过连续制药应用(即直接压片生产流程)来说明。这项工作还强调了对基于指数的指标的需求,这些指标能够从控制性能监测的角度量化和评估 PMM 和 CPD 的影响,通过根本原因分析帮助故障诊断,从而为连续生产应用的维护决策提供指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Hierarchical Approach to Monitoring Control Performance and Plant-Model Mismatch.

Controllers are often tuned during plant commissioning, with a fixed process model. However, over time degradation can occur in the process, the process model and the controller, making it necessary to either re-tune the controller or re-identify the process model. Authors have proposed a variety of approaches to identify plant-model mismatch (PMM) and control performance degradation (CPD). While each approach may have its own advantages and disadvantages, they are generally designed to function on different timescales. The differing timescales result in the need for a multi-level hierarchical approach to monitor, detect, and manage PMM and CPD, as illustrated through a continuous pharmaceutical manufacturing application, i.e., a direct compression tablet manufacturing process. This work also highlights the requirement for index-based metrics, that enable the impact of PMM and CPD to be quantified and assessed from a control performance monitoring perspective, to aid fault diagnosis through root cause analysis to guide maintenance decisions for continuous manufacturing applications.

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