2012 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE) 2012
DOI: 10.1109/date.2012.6176676
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An efficient framework for passive compact dynamical modeling of multiport linear systems

Abstract: We present an efficient and scalable framework for the generation of guaranteed passive compact dynamical models for multiport structures. The proposed algorithm enforces passivity using frequency independent linear matrix inequalities, as opposed to the existing optimization based algorithms which enforce passivity using computationally expensive frequency dependent constraints. We have tested our algorithm for various multiport structures. An excellent match between the given samples and our passive model wa… Show more

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Cited by 6 publications
(5 citation statements)
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References 12 publications
(57 reference statements)
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“…see Appendix C for a derivation. From (17), we note that h(x (0) ) − ∂h(x (0) ) T P LB ∂h(x (0) ) > 1 implies h(x) > 1 , which means that all points in ε LB are infeasible,…”
Section: A Initializationmentioning
confidence: 99%
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“…see Appendix C for a derivation. From (17), we note that h(x (0) ) − ∂h(x (0) ) T P LB ∂h(x (0) ) > 1 implies h(x) > 1 , which means that all points in ε LB are infeasible,…”
Section: A Initializationmentioning
confidence: 99%
“…Within these 'two-steps' methods, some approaches guarantee optimality in the second step exploiting convex or quasiconvex formulations ( [10]- [12], [14]- [17]). Such algorithms enforce passivity by defining constraints based on the positive real lemma or the bounded real lemma [39], [40].…”
mentioning
confidence: 99%
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“…they have negative real part ( 0). For our analysis, the model that minimizes the mismatch between the measured transconductance and output of the model using an optimization framework as described in [22,23].…”
Section: Temperature Stabilitymentioning
confidence: 99%
“…Convex relaxations to this problem are proposed in [1]- [4]. These algorithms rely on enforcing passivity by defining constraints for the positive real lemma or the bounded real lemma.…”
Section: Introductionmentioning
confidence: 99%