We present a general framework for the construction of guaranteed stable and passive multivariate macromodels from sampled frequency responses. The obtained macromodels embed in closed form the dependence on external parameters, through a data-driven approximation of input data samples based on orthogonal polynomial bases. The key novel contribution of this work is an extension to the multivariate and possibly high-dimensional case of Hamiltonian-based passivity check and enforcement algorithms, which can be applied to enforce both uniform stability and uniform passivity of the models. The modeling flow is demonstrated on a representative interconnect example.

Multivariate macromodeling with stability and passivity constraints / Zanco, Alessandro; Grivet-Talocia, S.; Bradde, Tommaso; DE STEFANO, Marco. - ELETTRONICO. - (2018), pp. 1-4. (Intervento presentato al convegno 22nd IEEE Workshop on Signal and Power Integrity, SPI 2018 tenutosi a Brest, France nel 22-25 May 2018) [10.1109/SaPIW.2018.8401664].

Multivariate macromodeling with stability and passivity constraints

ZANCO, ALESSANDRO;Grivet-Talocia, S.;BRADDE, TOMMASO;DE STEFANO, MARCO
2018

Abstract

We present a general framework for the construction of guaranteed stable and passive multivariate macromodels from sampled frequency responses. The obtained macromodels embed in closed form the dependence on external parameters, through a data-driven approximation of input data samples based on orthogonal polynomial bases. The key novel contribution of this work is an extension to the multivariate and possibly high-dimensional case of Hamiltonian-based passivity check and enforcement algorithms, which can be applied to enforce both uniform stability and uniform passivity of the models. The modeling flow is demonstrated on a representative interconnect example.
2018
9781538622995
File in questo prodotto:
File Dimensione Formato  
cnf-2018-spi-parametric.pdf

accesso aperto

Descrizione: Post-Print Author version
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: Pubblico - Tutti i diritti riservati
Dimensione 811.53 kB
Formato Adobe PDF
811.53 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2712915
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo