ROBUST DATA RECONCILIATION AND GROSS ERROR-DETECTION - THE MODIFIED MIMT USING NLP

Authors
KIM IW KANG MS PARK SW EDGAR TF
Citation
Iw. Kim et al., ROBUST DATA RECONCILIATION AND GROSS ERROR-DETECTION - THE MODIFIED MIMT USING NLP, Computers & chemical engineering, 21(7), 1997, pp. 775-782
Citations number
15
Categorie Soggetti
Computer Application, Chemistry & Engineering","Engineering, Chemical","Computer Science Interdisciplinary Applications
Journal title
Computers & chemical engineering → ACNP
ISSN journal
00981354
Volume
21
Issue
7
Year of publication
1997
Pages
775 - 782
Database
ISI
SICI code
0098-1354(1997)21:7<775:RDRAGE>2.0.ZU;2-H
Abstract
The Modified Iterative Measurement Test (MIMT) gross error detection a lgorithm has been improved using nonlinear programming techniques to i mprove its robustness and performance. Both data reconciliation and es timation of gross errors in MIMT can utilize nonlinear programming (NL P) techniques. The algorithm has been tested on a CSTR example and sho ws improved robustness compared to existing gross error detection algo rithms. Therefore this enhanced algorithm appears to be quite promisin g for data reconciliation and gross error detection of highly nonlinea r processes in chemical engineering. (C) 1997 Elsevier Science Ltd.