Principal Surface Model Based Quality Control Approach for Batch/Semi-Batch Processes

在工廠操作運行當中，對於系統狀態的量測和控制成功與否，經常是決定產品品質好壞的關鍵，而且也影響到工廠的操作安全，尤其在一些對環境變化敏感的反應程序，錯誤的資訊會導致控制器的失靈甚至進一步引發意外的發生，所以對於操作程序良好的監控和資訊數據的正確取得，是工廠程序操作中十分重要的一環。　然而由於許多工廠程序的操作條件特殊，如高溫高壓等，其線上的溫度、壓力及流量等量測器可能會產生量測誤差過大或甚至發生故障，因而導致控制上的困擾，影響控制。所以我們需要辨識系統變數間互動的關係，以建立系統變數的互動模式，進而利用模式來監視系統運作，並且以之對量測數據進行檢測和校正，以免錯誤的數據影響控制品質。　在此我們以主值分析法(PCA,Principal Component Analysis)及非線性主值分析法(NLPCA,Nonlinear Principal Component Analysis)分別針對模擬程序和真實實驗程序為例，來推求其變數間的互動關係，並建立起模式來為動態系統做監視及數據校正。

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並列摘要

Batch/semi-batch quality control has attracted much attention from chemical engineering researchers recently. In this work, a novel empirical model based quality control approach for batch processes is developed. The model implemented is based on independent nonlinear principal components obtained by means of principal surface analysis- a very hot topic in the area of statistical modeling. The partial initial conditions and intermediate measurements obtained from each batch are analyzed using this approach to extract the independent nonlinear principal components. An empirical model with the nonlinear principal components as inputs is built to predict product quality. Correcting actions based on the initial conditions and intermediate measurements are taken based on the predictions obtained using the empirical model. In this work, the problem formulation and solution method are presented. The illustrative examples include a simulation example and an experimental study on the batch reactive distillation process. The simulation and experimental results show that the proposed approach is highly promising.

並列關鍵字

Nonlinear principal components ； Principal surface ； MPC ； Optimization

國際替代計量

Principal Surface Model Based Quality Control Approach for Batch/Semi-Batch Processes

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