Zugl.: Hamburg, Techn. Univ., Diss., 2006

Zugl.: Hamburg, Techn. Univ., Diss., 2008

Tech. University, Diss., 2003--Chemnitz.

University, Diss., 2005--Köln.

We present a multi-grid method for a class of structured generalized Lyapunov matrix equations. Such equations need to be solved in each step of the Newton method for algebraic Riccati equations, which arise from linear-quadratic optimal control problems governed by partial differential equations. We prove the rate of convergence of the two-grid method to be bounded independent of the dimension of the problem under certain assumptions. The multi-grid method is based on matrix-matrix multiplications and thus it offers a great potential for a parallelization. The efficiency of the method is demonstrated by numerical experiments.

Continuing the previous work in the preprint 97-11 done for the 2D-approach in this paper we describe the Yserentant preconditioned conjugate gradient method as well as the BPX-preconditioned cg-iteration fastly solving 3D-elliptic boundary value problems on unstructured quasi uniform grids. These artificially constructed hierarchical methods have optimal computational costs. In the case of the sequential computing several numerical examples demonstrate their efficiency not depending on the finite element types used for the discretiziation of the original potential problem. Moreover, implementing the methods in parallel first results are given.

We present a multi-grid method for a class of structured generalized Lyapunov matrix equations. Such equations need to be solved in each step of the Newton method for algebraic Riccati equations, which arise from linear-quadratic optimal control problems governed by partial differential equations. We prove the rate of convergence of the two-grid method to be bounded independent of the dimension of the problem under certain assumptions. The multi-grid method is based on matrix-matrix multiplications and thus it offers a great potential for a parallelization. The efficiency of the method is demonstrated by numerical experiments.

Continuing the previous work in the preprint 97-11 done for the 2D-approach in this paper we describe the Yserentant preconditioned conjugate gradient method as well as the BPX-preconditioned cg-iteration fastly solving 3D-elliptic boundary value problems on unstructured quasi uniform grids. These artificially constructed hierarchical methods have optimal computational costs. In the case of the sequential computing several numerical examples demonstrate their efficiency not depending on the finite element types used for the discretiziation of the original potential problem. Moreover, implementing the methods in parallel first results are given.