Preconditioning Navier–Stokes control using multilevel sequentially semiseparable matrix computations

In this article, we study preconditioning techniques for the control of the Navier–Stokes equation, where the control only acts on a few parts of the domain. Optimization, discretization, and linearization of the control problem results in a generalized linear saddle-point system. The Schur complement for the generalized saddle-point system...

Preconditioning optimal in-domain control of navier-stokes equation using multilevel sequentially semiseparable matrix computations

In this manuscript, we study preconditioning techniques for optimal in-domain control of the Navier-Stokes equation, where the control only acts on a few parts of the domain. Optimization and linearization of the optimal in-domain control problem results in a generalized linear saddle-point system. The Schur complement for the generalized saddle...

Preconditioning Optimal Flow Control Problems Using Multilevel Sequentially Semiseparable Matrix Computations

Optimal flow control problems are important for applications in science and engineering. Solving such problems usually requires the solution of a large linear generalized saddle-point system. This linear system is sparse and highly indefinite. In order to solve such systems using Krylov subspace methods, efficient preconditioners are necessary...

Preconditioning Optimal In-Domain Control of Navier-Stokes Equation Using Multilevel Sequentially Semiseparable Matrix Computations

In this manuscript, we study preconditioning techniques for optimal in-domain control of the Navier-Stokes equation, where the control only acts on a few parts of the domain. Optimization and linearization of the optimal in-domain control problem results in a generalized linear saddle-point system. The Schur complement for the generalized saddle...