SVD/QR Based Model Error Indicator Function
Michael M. Yang, David L. Brown · 1997
A new model error indicator function based on singular value decomposition (SVD) and QR permutation decomposition techniques is proposed. Since an updating problem including large numbers of updating parameters is usuallyill-conditioned, a singular value decomposition technique is first used to determine the meaningful sub-matrix of the system data matrix. A QR permutation decomposition with column pivoting is then performed on this sub-matrix to find the permuted parameters. The equation error norms corresponding to sequential reduced systems are calculated and an error termination criterion is applied to determine the number of meaningful updating parameters. The proposed method is compared with two other popular error indicator functions. Test case includes a free-free supported beam structure.