Krylov subspace methods in control: an overview
Biswa Nath Datta
Abstract
Biswa Nath Datta
Abstract
There have been some developments in the area of large and sparse matrix computations. A class of classical methods known as the Krylov subspace methods that include the Lanczos and Arnoldi methods, have been found to be suitable for sparse matrix computations. We give a brief overview of some of the recently developed Arnoldi and Lanczos based methods that seem to be suitable for large and sparse control problems. The research in this area is still in its infancy.
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There have been some developments in the area of large and sparse matrix computations. A class of classical methods known as the Krylov subspace methods that include the Lanczos and Arnoldi methods, have been found to be suitable for sparse matrix computations. We give a brief overview of some of the recently developed Arnoldi and Lanczos based methods that seem to be suitable for large and sparse control problems. The research in this area is still in its infancy.
Key concepts: Krylov subspace, Lanczos resampling, Lanczos algorithm, Sparse matrix, Computation, Computer science, Generalized minimal residual method, Arnoldi iteration