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Recursive iterative Principal Component Analysis
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DOI：10.1016/j.compchemeng.2025.109170.png)
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Abstract
En 中文
• A recursive iterative PCA approach (RIPCA) is developed for the simultaneous identification of error variances and linear steady state models. • The recursive technique does not require past data to be stored and processes each sample of measurements as they are received. • Changes in the process resulting in time varying model order, model coefficients and/or error variances can be tracked and adapted to by this technique.
Keywords:
recursive iterative PCA
error variance identification
linear steady state models
adaptive tracking
model order变化
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