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Unbiased estimation in dynamic data reconciliation

Publication Type : Journal Article

Thematic Areas : Advanced Materials and Green Technologies

Publisher : Wiley Online Library

Source : AIChE journal, Wiley Online Library, Volume 39, Number 8, p.1330–1334 (1993)

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Campus : Coimbatore

School : School of Engineering

Center : Center for Excellence in Advanced Materials and Green Technologies

Department : Computer Science, Chemical, Civil

Year : 1993

Abstract : A computationally fast technique accurately estimates process variables when conditions are dynamic due to changes in steady states. The process variable estimators are unbiased and have known distributions. Thus, confidence intervals for true values of process variables are provided. The formulation of this technique was motivated by a recursive, dynamic data reconciliation technique that obtains very accurate estimators. These two techniques are compared in terms of computational speed and accuracy of estimators. The proposed technique is computationally faster, but not as accurate when variances of process measurements are large. However, the accuracy of the proposed estimators is shown to approach that of the recursive technique by iteratively recalculating estimates and when measurement variances decrease.

Cite this Research Publication : D. K. Rollins and Dr. Sriram Devanathan, “Unbiased estimation in dynamic data reconciliation”, AIChE journal, vol. 39, pp. 1330–1334, 1993.

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