On finding the matrix projection in the data reconciliation solution

Computers and Chemical Engineering

Volumn 22, Issue 11, 1998, Pages 1553-1557

  Kelly, Jeffrey Dean ^a  

^a St Andrews Road ^*  (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CHEMICAL ENGINEERING; MATRIX ALGEBRA; NUMERICAL METHODS; VECTORS;

CHOLESKY FACTORIZATION; DATA RECONCILIATION; RECURSIVE MATRIX INVERSION; SINGULAR VALUE DECOMPOSITION;

MATHEMATICAL TECHNIQUES;

DATA;

EID: 0032532852     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0098-1354(98)00236-1     Document Type: Article

References (9)

1. Albuquerque J.S., Biegler L.T. Data reconciliation and gross-error detection for dynamic systems. A.I.Ch.E. J. 42:1996;10.
2. Crowe C.M., Garcia Y.A., Hrymak A. Reconciliation of process flow rates by matrix projection, Part I. Linear case A.I.Ch.E.J. 29:1983;6.
3. Golub, G.H., Klema, V. and Stewart, G.W. (1976) Rank degeneracy and least squares problems. Technical Report TR-456, Stanford University.
4. Golub G.H., Van Loan C.F. Matrix Computations. 1983;The Johns Hopkins University Press, Baltimore, MA.
5. Householder A.S. The Theory of Matrices in Numerical Analysis. 1975;Dover, New York.
6. Press W.H., Vetterling W.T., Teukolsky S.A., Flannery B.P. Numerical Recipes in FORTRAN. The Art of Scientific Computing Second:1994;Cambridge University Press.
7. Sanchez M., Romagnoli J. Use of orthogonal transformations in data classification-reconciliation. Comput. Chem. Engng. 20:1996;5.
8. Swartz, C.L.E. (1989). Data reconciliation for generalized flowsheet applications. Amer. Chem. Soc. National Meeting, Dallas, Texas.
9. Tong H., Crowe C.M. Detection of gross errors in data reconciliation by principle components. A.I.Ch.E.J. 41:1995;7.