System identification and model order reduction for TLM analysis

D. Lukashevich, F. Coccetti, P. Russer

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

A system identification (SI) and Prony's model based algorithm for modelling and prediction of a time-domain transient response is introduced and applied to time-domain transmission line matrix (TLM) transient responses in order to extrapolate parameters of microwave circuits and accelerate the simulation process. Application of moment matching model order reduction (MOR) techniques to the TLM method is presented with emphasis placed on Krylov subspace methods based on the Lanczos process and its modifications. The Krylov subspace methods are attractive for MOR in the TLM framework because the construction of orthonormal and biorthogonal bases for correspondent Krylov subspaces can be carried out through a direct application of the implicit TLM solver. MOR applied to TLM allows one to generate a compact macromodel of a TLM-system and significantly reduce the computational time. The efficiency and advantages of the SI and MOR techniques are demonstrated through their applications to the full-wave analysis of different electromagnetic structures. In addition, a brief comparison of SI and MOR involved for modelling of a planar patch antenna is provided.

Original languageEnglish
Pages (from-to)75-92
Number of pages18
JournalInternational Journal of Numerical Modelling: Electronic Networks, Devices and Fields
Volume20
Issue number1-2
DOIs
StatePublished - Jan 2007

Keywords

  • Model order reduction
  • System identification
  • Transmission line matrix method

Fingerprint

Dive into the research topics of 'System identification and model order reduction for TLM analysis'. Together they form a unique fingerprint.

Cite this