一种实现导纳矩阵宏模型无源性的快速方法

doi:10.3969/j.issn.1001-2400.2011.01.025

Abstract

Abstract:

Based on inequality constraint, numerical optimization is used in the traditional quadratic programming method to compensate the passivity violations, with the required simulation time being quite large. A novel quadratic programming method to enforce the passivity of macromodels is presented, which can greatly reduce the simulation time. This method is based on the quadratic programming method with an equality constraint. The associated optimization problem can be solved by the method of Lagrange multipliers. The Krylov subspace method is adopted to solve the resulting linear system, which can fully utilize the sparsity of the problem. The computational time required for this method is significantly reduced. A frequency selection strategy for passivity violations is also introduced. Several examples show that the solving time required for the presented method is less than 1/10 that of the traditional quadratic programming method.

Key words: macromodels, passivity, quadratic programming, Lagrange multipliers, sparsity

YAN Xu;LI Yushan;GAO Song;DING Tonghao;QU Yongzhe. Fast method to enforce the passivity of macromodels for the admittance matrix[J].J4, 2011, 38(1): 153-158.

References

[1] Gustavsen B, Semlyen A. Rational Approximation of Frequency Domain Responses by Vector Fitting[J]. IEEE Trans on Power Delivery, 1999, 14(3): 1052-1061.
[2] Deschrijver D, Mrozowski M, Dhaene T, et al. Macromodeling of Multiport Systems Using a Fast Implementation of the Vector Fitting Method[J]. IEEE Microwave Wireless Components Letters, 2008,18(6): 383-385.
[3] Ramirez A. Vector Fitting-Based Calculation of Frequency-Dependent Network Equivalents by Frequency Partitioning and Model-Order Reduction[J]. IEEE Trans on Power Delivery, 2009, 24(1): 410-415.
[4] Saraswat D, Achar R, Nakhla M. Global Passivity Enforcement Algorithm for Macromodels of Interconnect Subnetworks Characterized by Tabulated Data[J]. IEEE Trans on VLSI Systems, 2005, 13(7): 819-832.
[5] Triverio P, Grivet-Talocia S, Nakhla M. Stability, Causality, and Passivity in Electrical interconnect models[J]. IEEE Trans on Advanced Packaging, 2007, 3(4): 795-808.
[6] Coelho C P, Phillips J, Silveira L M. A Convex Programming Approach for Generating Guaranteed Passive Approximations to Tabulated Frequency-Data[J]. IEEE Trans on Computer-Aided Design of Integrated Circuits and System, 2004, 23(2): 293-301.
[7] Gustavsen B, Semlyen A. Enforcing Passivity for Admittance Matrices Approximated by Rational Functions[J]. IEEE Trans on Power Systems, 2001, 16,(2): 97-104.
[8] Gustavsen B. Computer Code for Passivity Enforcement of Rational Macromodels by Residue Perturbation[J]. IEEE Trans on Advanced Packaging, 2007, 23(4): 2278-2285.
[9] Grivet-Talocia S. Passivity Enforcement via Perturbation of Hamiltonian Matrices[J]. IEEE Trans on Circuits and Systems-I: Regular Paper, 2004, 51(9): 1755-1769.
[10] Grivet-Talocia S. An Adaptive Sampling Technique for Passivity Characterization and Enforcement of Large Interconnect Macromodels[J]. IEEE Trans on Advanced Packaging, 2007, 30(2): 226-237.
[11] Grivet-Talocia S, Ubolli A. A Comparative Study of Passivity Enforcement Schemes for Linear Lumped Macromodels[J]. IEEE Trans on Advanced Packaging, 2008, 31(4): 673-683.
[12] Swaminathan M, Engin A E. 芯片及系统的电源完整性建模与设计[M]. 李玉山, 张木水,译. 北京:电子工业出版社, 2009: 179-182.
[13] Semlyen A, Gustavsen B. A Half-Size Singularity Test Matrix for Fast and Reliable Passivity Assessment of Rational Models[J]. IEEE Trans on Power Delivery, 2009, 24(1): 345-351.
[14] Deschrijver D, Dhaene T, Modified Half-Size Test Matrix for Robust Passivity Assessment of S-Parameter Macromodels[J]. IEEE Microwave Wireless Components Letters, 2009, 19(5): 263-265.
[15] Grivet-Talocia S, Ubolli A. On the Generation of Large Passive Macromodels for Complex Interconnect Structures [J]. IEEE Trans on Advanced Packaging, 2006, 29(1): 39-54.
[16] Bai Z, Demmel J, Dongarra J, et al. Templates for the Solution of Algebraic Eigenvalue Problems: A Practical Guide[M]. Philadelphia: SIAM, 2000: 211-235.
[17] Horn R A, Johnson C R. Topics in Matrix Analysis[M]. New York: Cambridge University, 1991: 244-245.

Fast method to enforce the passivity of macromodels for the admittance matrix

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 10

Metrics

Comments

Recommended 0

[1]	CHEN Baojia,HE Wangpeng,HU Jie,WANG Geng,GUO Baolong. Method for diagnosis of data-driven GMC sparse enhancement [J]. Journal of Xidian University, 2019, 46(4): 74-79.
[2]	FENG Likang;HOU Ronghui. ICIC and CoMP based interference management scheme in small cell networks [J]. Journal of Xidian University, 2017, 44(5): 32-38.
[3]	YANG Wei;LIU Hongqing;LI Yong;ZHOU Yi. Joint estimation algorithms based on LMS and RLS in the presence of impulsive noise [J]. Journal of Xidian University, 2017, 44(2): 165-170.
[4]	YU Hongbo;FENG Dazheng;XIE Hu. Iterative dimension-reduced robust adaptive beamformer for MIMO radar [J]. J4, 2016, 43(1): 30-35.
[5]	LI Quanhe;ZHA Yufei;XIONG Lei;BI Duyan. Novel method for haze degraded image scene rendition [J]. J4, 2013, 40(5): 99-106.
[6]	YAN Xu;LI Yushan;DING Tonghao;QU Yongzhe;JIANG Dongchu;LU Jianmin. Passivity enforcement scheme for descriptor systems [J]. J4, 2013, 40(3): 188-193+220.
[7]	XU Gang;CHEN Qianqian;HOU Yuxing;LI Yachao;XING Mengdao. Super-resolution imaging of forward-looking scan SAR [J]. J4, 2012, 39(5): 79-84+95.
[8]	GAO Song;LI Yushan;YAN Xu. Fast convex optimization method for passivity enforcement of macromodels [J]. J4, 2012, 39(1): 62-66+121.
[9]	. Image restoration model and algorithms with second-generation curvelets [J]. J4, 2009, 36(6): 1092-1096.
[10]	WANG Ling(1);BO Lie-feng(1);LIU Fang(2);JIAO Li-cheng(1). Sparse hidden space support vector machine [J]. J4, 2006, 33(6): 896-901.