Improving the Convergence of Vector Fitting for Equivalent Circuit Extraction From Noisy Frequency Responses

The vector fitting (VF) algorithm has become a common tool in electromagnetic compatibility and signal integrity studies. This algorithm allows the derivation of a rational approximation to the transfer matrix of a given linear structure starting from measured or simulated frequency responses. This paper addresses the convergence properties of a VF when the frequency samples are affected by noise.We show that small amounts of noise can seriously impair or destroy convergence. This is due to the presence of spurious poles that appear during the iterations. To overcome this problem we suggest a simple modification of the basic VF algorithm, based on the identification and removal of the spurious poles. Also, an incremental pole addition and relocation process is proposed in order to provide automatic order estimation even in the presence of significant noise.We denote the resulting algorithm as vector fitting with adding and skimming (VF-AS). A thorough validation of the VF-AS algorithm is presented using a Monte Carlo analysis on synthetic noisy frequency responses. The results show excellent convergence and significant improvements with respect to the basic VF iteration scheme. Finally, we apply the new VF-AS algorithm to measured scattering responses of interconnect structures and networks typical of high-speed digital systems

Gain scheduled control strategies for a nonlinear electrostatic microgripper: Design and real time implementation

International audienceThis paper deals with the accurate and fast positioning control of a nonlinear electrostatically actuated microgripper. Considering the importance of nonlinearities, performances are achieved through the design of gain scheduled controllers. To this end, a nonlinear model of the studied system is proposed and is reformulated into a polynomial LPV (Linear Parameter Varying) model. Controllers are designed considering the particular polynomial parametric dependence of the LPV model. In a first instance, a controller is synthesized using an affine LPV descriptor representation of the system and LMI (Linear Matrix Inequality) constraints. In a second instance, to deal with real time implementation constraints, a second controller is designed based on an iterative procedure using the eigenstructure assignment methodology and a worst case analysis. For embedded applications, requiring simplecontroller structures, we show experimentally the interest of the iterative procedure which can achieve good results relatively with the ones obtained using recent advances of robust controllers based on LMI conditions

On the Generation of Large Passive Macromodels for Complex Interconnect Structures

This paper addresses some issues related to the passivity of interconnect macromodels computed from measured or simulated port responses. The generation of such macromodels is usually performed via suitable least squares fitting algorithms. When the number of ports and the dynamic order of the macromodel is large, the inclusion of passivity constraints in the fitting process is cumbersome and results in excessive computational and storage requirements. Therefore, we consider in this work a post-processing approach for passivity enforcement, aimed at the detection and compensation of passivity violations without compromising the model accuracy. Two complementary issues are addressed. First, we consider the enforcement of asymptotic passivity at high frequencies based on the perturbation of the direct coupling term in the transfer matrix. We show how potential problems may arise when off-band poles are present in the model. Second, the enforcement of uniform passivity throughout the entire frequency axis is performed via an iterative perturbation scheme on the purely imaginary eigenvalues of associated Hamiltonian matrices. A special formulation of this spectral perturbation using possibly large but sparse matrices allows the passivity compensation to be performed at a cost which scales only linearly with the order of the system. This formulation involves a restarted Arnoldi iteration combined with a complex frequency hopping algorithm for the selective computation of the imaginary eigenvalues to be perturbed. Some examples of interconnect models are used to illustrate the performance of the proposed technique

A two-step method for retrieving the longitudinal profile of an electron bunch from its coherent radiation

The coherent radiation emitted by an electron bunch provides a diagnostic signal that can be used to estimate its longitudinal distribution. Commonly only the amplitude of the intensity spectrum can be measured and the associated phase must be calculated to obtain the bunch profile. Very recently an iterative method was proposed to retrieve this phase. However ambiguities associated with non-uniqueness of the solution are always present in the phase retrieval procedure. Here we present a method to overcome the ambiguity problem by first performing multiple independent runs of the phase retrieval procedure and then second, sorting the good solutions by mean of cross-correlation analysis. Results obtained with simulated bunches of various shapes and experimental measured spectra are presented, discussed and compared with the established Kramers-Kronig method. It is shown that even when the effect of the ambiguities is strong, as is the case for a double peak in the profile, the cross-correlation post-processing is able to filter out unwanted solutions. We show that, unlike the Kramers-Kronig method, the combined approach presented is able to faithfully reconstruct complicated bunch profiles.Comment: 22 pages, 5 figure

On the use of rational-function fitting methods for the solution of 2D Laplace boundary-value problems

A computational scheme for solving 2D Laplace boundary-value problems using rational functions as the basis functions is described. The scheme belongs to the class of desingularized methods, for which the location of singularities and testing points is a major issue that is addressed by the proposed scheme, in the context of the 2D Laplace equation. Well-established rational-function fitting techniques are used to set the poles, while residues are determined by enforcing the boundary conditions in the least-squares sense at the nodes of rational Gauss-Chebyshev quadrature rules. Numerical results show that errors approaching the machine epsilon can be obtained for sharp and almost sharp corners, nearly-touching boundaries, and almost-singular boundary data. We show various examples of these cases in which the method yields compact solutions, requiring fewer basis functions than the Nystr\"{o}m method, for the same accuracy. A scheme for solving fairly large-scale problems is also presented

A Perturbation Scheme for Passivity Verification and Enforcement of Parameterized Macromodels

This paper presents an algorithm for checking and enforcing passivity of behavioral reduced-order macromodels of LTI systems, whose frequency-domain (scattering) responses depend on external parameters. Such models, which are typically extracted from sampled input-output responses obtained from numerical solution of first-principle physical models, usually expressed as Partial Differential Equations, prove extremely useful in design flows, since they allow optimization, what-if or sensitivity analyses, and design centering. Starting from an implicit parameterization of both poles and residues of the model, as resulting from well-known model identification schemes based on the Generalized Sanathanan-Koerner iteration, we construct a parameter-dependent Skew-Hamiltonian/Hamiltonian matrix pencil. The iterative extraction of purely imaginary eigenvalues ot fhe pencil, combined with an adaptive sampling scheme in the parameter space, is able to identify all regions in the frequency-parameter plane where local passivity violations occur. Then, a singular value perturbation scheme is setup to iteratively correct the model coefficients, until all local passivity violations are eliminated. The final result is a corrected model, which is uniformly passive throughout the parameter range. Several numerical examples denomstrate the effectiveness of the proposed approach.Comment: Submitted to the IEEE Transactions on Components, Packaging and Manufacturing Technology on 13-Apr-201

Reconstruction and Particle Identification for a DIRC System

We study the reconstruction and particle identification (PID) problem for Ring Imaging devices providing a good knowledge of the direction of the Cerenkov photons, as the DIRC system, on which we specialize. We advocate first the use of the stereographic projection as a tool allowing a suitable representation of the photon data, as it allows to represent the Cerenkov cone always as a circle. We set up an algorithm able to perform reliably a fit of circle arcs of small angular opening, by minimising a true Chi2 expression. The system we develop for PID relies on this algorithm and on a procedure able to remove background photons with a high efficiency. We thus show that, even when the background is large, it is possible to perform an efficient PID by means of a fit algorithm which finally provides all the circle parameters; these are connected with the charged track direction and its Cerenkov angle. It is shown that background effects can be dealt without spoiling significantly the reconstruction probability distributions.Comment: 67 pages, 23 figure