Journal ArticleDOI
A Quasi-Convex Optimization Approach to Parameterized Model Order Reduction
TLDR
An optimization based model order reduction (MOR) framework is proposed that involves setting up a quasi-convex program that explicitly minimizes a relaxation of the optimal H/sub /spl infin// norm MOR problem.Abstract:
In this paper, an optimization-based model order reduction (MOR) framework is proposed. The method involves setting up a quasi-convex program that solves a relaxation of the optimal Hinfin norm MOR problem. The method can generate guaranteed stable and passive reduced models and is very flexible in imposing additional constraints such as exact matching of specific frequency response samples. The proposed optimization-based approach is also extended to solve the parameterized model-reduction problem (PMOR). The proposed method is compared to existing moment matching and optimization-based MOR methods in several examples. PMOR models for large RF inductors over substrate and power-distribution grid are also constructed.read more
Citations
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Journal ArticleDOI
Perspectives on System Identification
TL;DR: This presentation aims at giving an overview of the “science” side of System identification, i.e. basic principles and results and at pointing to open problem areas in the practical, “art”, side of how to approach and solve a real problem.
Journal ArticleDOI
Control-Oriented Thermal Modeling of Multizone Buildings: Methods and Issues: Intelligent Control of a Building System
Ercan Atam,Lieve Helsen +1 more
TL;DR: The residential and commercial building sector is known to use around 40% of the total end-use energy and is considered to be the largest energy consumer sector in the world as mentioned in this paper.
Journal ArticleDOI
Stable Reduced Models for Nonlinear Descriptor Systems Through Piecewise-Linear Approximation and Projection
Bradley N. Bond,Luca Daniel +1 more
TL;DR: In this article, the authors present theoretical and practical results concerning the stability of piecewise-linear (PWL) reduced models for the purposes of analog macromodeling.
Journal ArticleDOI
Model Order Reduction of Parameterized Interconnect Networks via a Two-Directional Arnoldi Process
TL;DR: PIMTAP model yields the same form of the original state equations and preserves the passivity of parameterized R LC networks like the well-known method passive reduced-order interconnect macromodeling algorithm for nonparameterized RLC networks.
Journal ArticleDOI
Compact Modeling of Nonlinear Analog Circuits Using System Identification via Semidefinite Programming and Incremental Stability Certification
Bradley N. Bond,Zohaib Mahmood,Yan Li,Ranko Sredojevic,Alexandre Megretski,Vladimir Stojanovi,Yehuda Avniel,Luca Daniel +7 more
TL;DR: Numerical results are presented and it is shown that dynamical models can accurately predict important circuit performance metrics, and may thus, be useful for design optimization of analog systems.
References
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Book
Robust and Optimal Control
TL;DR: This paper reviewed the history of the relationship between robust control and optimal control and H-infinity theory and concluded that robust control has become thoroughly mainstream, and robust control methods permeate robust control theory.
Journal ArticleDOI
Rational approximation of frequency domain responses by vector fitting
Bjorn Gustavsen,Adam Semlyen +1 more
TL;DR: The paper describes a general methodology for the fitting of measured or calculated frequency domain responses with rational function approximations by replacing a set of starting poles with an improved set of poles via a scaling procedure.
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