Generalized T distribution and its applications to process data reconciliation and process monitoring
Document Type
Article
Publication Date
1-1-2005
Abstract
Process data are conventionally characterized by normal distribution and techniques based on this assumption could suffer performance and efficiency losses when the assumption is violated. In this paper, the generalized T distribution is introduced and its robustness characteristics are investigated. Using this probability density function to characterize the process data, it is shown that both efficiency as well as robustness of some of the techniques currently employed in process systems engineering can be improved. Performance is illustrated by its applications to process data reconciliation and process fault detection of chemical engineering case studies. © 2005, Sage Publications. All rights reserved.
Publication Source (Journal or Book title)
Transactions of the Institute of Measurement & Control
First Page
367
Last Page
390
Recommended Citation
Wang, D., & Romagnoli, J. (2005). Generalized T distribution and its applications to process data reconciliation and process monitoring. Transactions of the Institute of Measurement & Control, 27 (5), 367-390. https://doi.org/10.1191/0142331205tm155oa