DATA RECONCILIATION FOR INPUT-OUTPUT MODELS IN LINEAR DYNAMIC SYSTEMS

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 468
  • Download : 20
DC FieldValueLanguage
dc.contributor.authorKim, In-Won-
dc.contributor.authorPark, Sunwon-
dc.contributor.authorEdgar, Thomas F.-
dc.date.accessioned2011-09-29T01:22:24Z-
dc.date.available2011-09-29T01:22:24Z-
dc.date.issued1996-
dc.identifier.citationKorean Journal of Chemical Engineering, Vol.13, No.2, pp.211-215en
dc.identifier.urihttp://hdl.handle.net/10203/25288-
dc.description.abstractSequential data reconciliation algorithms have been developed for input-output models in linear dynamic systems. Existing filtering methods do not treat the case where there are measurement errors in the input variables. In our apporoach, the measurement errors in the input variables are optimally handled by the least squares method. This method show good performance for input-output models.en
dc.description.sponsorshipThe authors gratefully acknowledge the support from the Automation Research Center ar POSTEC and the KOSEF Grant 94-1400-01-01-3.en
dc.language.isoen_USen
dc.publisher한국화학공학회en
dc.subjectData Reconciliationen
dc.subjectLeast-squares Estimationen
dc.titleDATA RECONCILIATION FOR INPUT-OUTPUT MODELS IN LINEAR DYNAMIC SYSTEMSen
dc.typeArticleen
Appears in Collection
CBE-Journal Papers(저널논문)

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0