D.P. Papadopoulos

TL;DR: In this article, the Pade approximation method, coupled with three powerful dominant pole selection criteria, is introduced for the purpose of application to the high degree matrix transfer function (which may be derived by the application of the Leverrier algorithm to the MIMO linear time-invariant state-space representation) of the original system and obtaining corresponding adequate reduced-order model(s).

TL;DR: In this article, two frequency-domain reduction (approximation) methods are introduced, for the purpose of applying them to high-degree transfer functions of single-input single-output linear time-invariant systems and obtain corresponding reduced order models.

TL;DR: In this article, the combined use of the time moment and Pade approximation methods (in time space and frequency domain description), coupled with three powerful dominant pole selection criteria, is introduced for the purpose of application to high-order MIMO linear time-invariant state-space original system models, in order to obtain corresponding adequate reduced order model(s).

TL;DR: In this article, a mixed method of model-order reduction is introduced, which is based on the linear state-space representation of the original system, and the derivation of its transfer function matrix expression uses the Leverrier algorithm and the application of well known partial-fraction expansion techniques together with the concept of dominant eigenvalues on the transfer function of the system.

TL;DR: In this article, the Routh frequency-domain reduction (approximation) method, coupled with powerful dominant pole-selection criteria, is introduced for the purpose of application to high-degree transfer functions of MIMO linear time-invariant systems to obtain corresponding adequate reduced-order models.