Please use this identifier to cite or link to this item: https://doi.org/10.1016/S1570-7946(04)80178-0
Title: A Robust Strategy for Joint Data Reconciliation and Parameter Estimation
Authors: Joe, Y.Y.
Wang, D.
Ching, C.B.
Tay, A. 
Ho, W.K. 
Romagnoli, J.
Keywords: data reconciliation
error-in-all-variables
estimators
parameter estimation
robust
Issue Date: 2004
Source: Joe, Y.Y.,Wang, D.,Ching, C.B.,Tay, A.,Ho, W.K.,Romagnoli, J. (2004). A Robust Strategy for Joint Data Reconciliation and Parameter Estimation. Computer Aided Chemical Engineering 18 (C) : 673-678. ScholarBank@NUS Repository. https://doi.org/10.1016/S1570-7946(04)80178-0
Abstract: In this work, the generalized T (GT) distribution is used to develop a statistically robust joint data reconciliation - parameter estimation (DRPE) strategy. The robustness feature is provided by the GT distribution, which includes Normal, Laplacian and Cauchy distribution as special cases. We use historical data to first estimate the parameters of the GT distribution, so that the resulting estimator is efficient when the error is in the GT family. The strategy is implemented in a simulation of a practical chemical engineering plant. The results confirm the robustness and efficiency of the estimator. © 2004 Elsevier B.V. All rights reserved.
Source Title: Computer Aided Chemical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/54797
ISSN: 15707946
DOI: 10.1016/S1570-7946(04)80178-0
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