Passivity Of Macromodels Research Articles

Delay-extraction-based sensitivity analysis of multiconductor transmission lines with nonlinear terminations

An efficient approach is presented for time-domain sensitivity analysis of lossy multiconductor transmission lines with respect to electrical and/or physical parameters. The proposed method employs delay extraction prior to approximating the matrix exponential stamp of the line and guarantees macromodel passivity. A delay-extraction-based equivalent circuit for sensitivity analysis is derived in a closed form, leading to significant computational advantages.

Passivity verification in delay-based macromodels of electrical interconnects

This paper presents a new theory that addresses the issue of passivity in macromodels of electrical interconnects constructed based on the method of characteristics (MoC). The proposed approach develops a new algebraic test to check for passivity in macromodels generated using MoC. The theory behind the developed test is based on deriving the necessary and sufficient conditions for the loss of positive-realness in the admittance matrix of the developed macromodel. An algorithmic procedure is proposed to verify passivity of general macromodels derived from the MoC. The results presented in this paper can be employed to test for positive-realness in dynamical systems described by algebraic delay-differential equations with discrete commensurate delays.

Passive Reduction Algorithm for RLC Interconnect Circuits With Embedded State-Space Systems (PRESS)

With the increasing operating frequencies and functionality in modern designs, the resulting size of circuit equations of high-frequency interconnect and microwave subnetworks are becoming large. Model-order reduction-based algorithms were recently suggested to handle the solution complexity of such circuits. The major objectives in state-of-the-art model-reduction algorithms are: 1) achieving accurate and compact models; 2) numerically stable and efficient generation of models; and 3) preservation of system properties such as passivity. Algorithms such as PRIMA generate guaranteed passive reduced-order models for large interconnect circuits described by RLC type of circuits. However, with the diverse technologies and complex geometries, it is becoming prevalent to describe some of the embedded linear modules in terms of state-space equations. In this paper, we show how to extend the scope of PRIMA-type first-level reduction algorithms for simultaneous reduction of combined circuits containing both RLC interconnects and embedded modules described by general passive state-space equations, while preserving the passivity of the resulting reduced-order model. Necessary formulation, proof of macromodel passivity, and validation examples are given.

Passive interconnect reduction algorithm for distributed/measured networks

This paper presents an efficient algorithm for the transient simulation of multiport distributed interconnect networks in the presence of nonlinear subcircuits. The proposed multilevel multipoint model-reduction algorithm combines the merits of recently proposed Krylov-space techniques and block complex frequency-hopping to generate compact time-domain macromodels. The method overcomes the difficulty of slower transient simulation caused by redundant poles in reduced-order models obtained by Krylov-space methods. Also, it provides an efficient means to translate Krylov-space-based reduced models of distributed/measured networks with frequency-dependent descriptions into time-domain macromodels. In addition, a strategy to preserve the passivity of macromodels during multilevel reduction is presented. An important advantage of the proposed algorithm is that it can directly handle distributed stamps such as transmission lines described by Telegrapher's equations, frequency-dependent parameters, full-wave, and measured subnetworks.

PRIMA: passive reduced-order interconnect macromodeling algorithm

This paper describes an algorithm for generating provably passive reduced-order N-port models for RLC interconnect circuits. It is demonstrated that, in addition to macromodel stability, macromodel passivity is needed to guarantee the overall circuit stability once the active and passive driver/load models are connected. The approach proposed here, PRIMA, is a general method for obtaining passive reduced-order macromodels for linear RLC systems. In this paper, PRIMA is demonstrated in terms of a simple implementation which extends the block Arnoldi technique to include guaranteed passivity while providing superior accuracy. While the same passivity extension is not possible for MPVL, comparable accuracy in the frequency domain for all examples is observed.