An Iterative Eigenvector Tangential Interpolation Algorithm for large-scale LTI and a class of LPV model approximation

In this paper, a new Iterative Eigenvector Tangential Interpolation Algorithm (IETIA) is proposed to approximate large-scale LTI models, allowing to achieve ℌ
₂
optimality-like conditions while preserving some user-defined eigenvalues. The proposed algorithm is also shown to be applicable to a certain class of LPV models. Numerical applications on standard model reduction benchmarks assess the effectiveness of the approach.