The ADI iteration for Lyapunov equations implicitly performs H2 pseudo-optimal model order reduction

Two approaches for approximating the solution of large-scale Lyapunov equations are considered: the alternating direction implicit (ADI) iteration and projective methods by Krylov subspaces. A link between them is presented by showing that the ADI iteration can always be identified by a Petrov-Galerkin projection with rational block Krylov subspaces. Then a unique Krylov-projected dynamical system can be associated with the ADI iteration, which is proven to be an H2 pseudo-optimal approximation. This includes the generalization of previous results on H2 pseudo-optimality to the multivariable case. Additionally, a low-rank formulation of the residual in the Lyapunov equation is presented, which is well-suited for implementation, and which yields a measure of the "obliqueness" that the ADI iteration is associated with.

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