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Proceedings ArticleDOI

An efficient algorithm for frequency-weighted balanced truncation of VLSI interconnects in descriptor form

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TLDR
An efficient frequency-weighted balanced truncation algorithm without finding the spectral projectors is proposed that is accurate and efficient and used to ensure passivity of RLC interconnect models.
Abstract
Balanced truncation of descriptor systems requires computation of spectral projectors and solution of the generalized projected Lyapunov equations, both of which have significant complexity. Frequency-weighted balancing methods are more efficient if the response over a specific frequency range is desired. However, a direct extension of these methods to descriptor systems requires the spectral projectors. In this paper, we propose an efficient frequency-weighted balanced truncation algorithm without finding the spectral projectors. Samples of the frequency-domain solution to the system are used to get an accurate estimate of the improper Gramians. The proper Gramians are computed after adjusting for the contribution of the improper subsystem. Low rank factors of these Gramians are used to obtain a basis that includes the contribution of both the proper and improper subsystems. Congruence transform is used to ensure passivity of RLC interconnect models. Results for standard benchmarks show that the method is accurate and efficient.

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References
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Computer-aided design

TL;DR: This project is engaged in a program of research into the application of the concepts and techniques of modern data processing to the design of mechanical parts and the further development of automatic programming systems for numerically controlled machine tools.
Journal ArticleDOI

Model reduction in limited time and frequency intervals

TL;DR: In this article, the controllability and observability grammars in limited time and frequency intervals are used for model reduction in stable and unstable systems, and a near-optimal model reduction procedure is proposed.
Journal ArticleDOI

Gramian-Based Model Reduction for Descriptor Systems

TL;DR: This work considers model reduction methods for linear time-invariant continuous-time descriptor systems based on the balanced truncation technique and closely related to the controllability and observability Gramians and Hankel singular values of descriptor systems.
Journal ArticleDOI

Gramian-Based Reduction Method Applied to Large Sparse Power System Descriptor Models

TL;DR: An efficient linear system reduction method that computes approximations to the controllability and observability gramians of large sparse power system descriptor models by exploiting the fact that a Lyapunov equation solution can be decomposed into low-rank Choleski factors, which are determined by the alternating direction implicit (ADI) method.
Journal ArticleDOI

Poor man's TBR: a simple model reduction scheme

TL;DR: A model reduction algorithm motivated by a connection between frequency-domain projection methods and approximation of truncated balanced realizations that can outperform the standard order reduction techniques by providing similar accuracy with lower order models or superior accuracy for the same size model.
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