A proximal point-like method for symmetric finite element model updating problems

Abstract

The matrix model updating problem (MUP), considered in this paper, concerns updating a symmetric second-order finite element model so that the updated model reproduces a set of measured or given eigenvalues and eigenvectors, and preserves the symmetry, positive semidefiniteness and sparsity of the original model simultaneously. By exploiting the special structure offered by the constraint set, the optimization problem for MUP is formulated in such a way that the proximal point-like method can be used to solve the equivalent problem. We show that the proposed method converges globally and numerical results show that the proposed method works well for incomplete measured data.