A New Preconditioning Strategy for Solving a Class of Time-Dependent PDE-Constrained Optimization Problems

Authors

  • Minli Zeng & Guofeng Zhang

DOI:

https://doi.org/10.4208/jcm.1401-CR3

Keywords:

PDE-constrained optimization, Reduced linear system of equations, Preconditioning, Saddle point problem, Krylov subspace methods.

Abstract

In this paper, by exploiting the special block and sparse structure of the coefficient matrix, we present a new preconditioning strategy for solving large sparse linear systems arising in the time-dependent distributed control problem involving the heat equation with two different functions. First a natural order-reduction is performed, and then the reduced-order linear system of equations is solved by the preconditioned MINRES algorithm with a new preconditioning techniques. The spectral properties of the preconditioned matrix are analyzed. Numerical results demonstrate that the preconditioning strategy for solving the large sparse systems discretized from the time-dependent problems is more effective for a wide range of mesh sizes and the value of the regularization parameter.

Published

2018-08-22

Issue

Section

Articles