Process control based on PCA models. Abstract: In this paper an approach to design controllers based on principal components analysis (PCA) models is presented.
In this paper an approach to design controllers based on principal components analysis (PCA) models is presented. Closed-loop control can be formulated and ...
In this paper an approach to design controllers based on principal components analysis (PCA) models is presented. Closed-loop control can be formulated and.
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Although principal components analysis (PCA) has shown some utility as a multivariate statistical process control. (MSPC) tool, a theoretical basis for its use ...
This paper introduces model-based PCA that accounts for the non-linearity of a process by using known physical relations between process variables.
The main procedures used to implement this MSPC-PCA analysis are the following: computing eigenvectors and eigenvalues; choosing the number of com- ponents of ...
Palma, L., F. Coito, R. N. d Silva, and P. Gil. "Process Control Based on PCA Models." 15th IEEE International Conference on Emerging Technologies and Factory ...
When using PCA model, two statistics are constructed to interpret the mean and variance information of process, known as T2 statistic and Q (also known as ...
Jun 18, 2019 · This article proposes a distributed principal component analysis method based on the angle-relevant variable selection for plant-wide process ...
Mar 21, 2024 · PCA is one of the more common forms of predictive modeling in manufacturing. PCA stands for Principal Component Analysis. A PCA model is a way ...