Parameterized macromodeling of passive and active dynamical systems

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Identifying Position-Dependent Mechanical Systems: A Modal Approach Applied to a Flexible Wafer Stage

Increasingly stringent performance requirements for motion control necessitate the use of increasingly detailed models of the system behavior. Motion systems inherently move, therefore, spatio-temporal models of the flexible dynamics are essential. In this paper, a two-step approach for the identification of the spatio-temporal behavior of mechanical systems is developed and applied to a lightweight prototype industrial wafer stage. The proposed approach exploits a modal modeling framework and combines recently developed powerful linear time invariant (LTI) identification tools with a spline-based mode-shape interpolation approach to estimate the spatial system behavior. The experimental results for the wafer stage application confirm the suitability of the proposed approach for the identification of complex position-dependent mechanical systems, and its potential for motion control performance improvements

Gaussian inference for data-driven state-feedback design of nonlinear systems

Data-driven control of nonlinear systems with rigorous guarantees is a challenging problem as it usually calls for nonconvex optimization and requires often knowledge of the true basis functions of the system dynamics. To tackle these drawbacks, this work is based on a data-driven polynomial representation of general nonlinear systems exploiting Taylor polynomials. Thereby, we design state-feedback laws that render a known equilibrium point globally asymptotically stable while operating with respect to a desired quadratic performance criterion. The calculation of the polynomial state feedback boils down to a single sum-ofsquares optimization problem, and hence to computationally tractable linear matrix inequalities. Moreover, we examine state-input data in presence of Gaussian noise by Bayesian inference to overcome the conservatism of deterministic noise characterizations from recent data-driven control approaches for Gaussian noise.Comment: Final version, accepted for presentation at the 22nd IFAC World Congress, 202

Advancements of MultiRate Signal processing for Wireless Communication Networks: Current State Of the Art

With the hasty growth of internet contact and voice and information centric communications, many contact technologies have been urbanized to meet the stringent insist of high speed information transmission and viaduct the wide bandwidth gap among ever-increasing high-data-rate core system and bandwidth-hungry end-user complex. To make efficient consumption of the limited bandwidth of obtainable access routes and cope with the difficult channel environment, several standards have been projected for a variety of broadband access scheme over different access situation (twisted pairs, coaxial cables, optical fibers, and unchanging or mobile wireless admittance). These access situations may create dissimilar channel impairments and utter unique sets of signal dispensation algorithms and techniques to combat precise impairments. In the intended and implementation sphere of those systems, many research issues arise. In this paper we present advancements of multi-rate indication processing methodologies that are aggravated by this design trend. The thesis covers the contemporary confirmation of the current literature on intrusion suppression using multi-rate indication in wireless communiquE9; networks

In vitro generation of human innate lymphoid cells from CD34+ hematopoietic progenitors recapitulates phenotype and function of ex vivo counterparts

Angeborene lymphatische Zellen (ILC) sind wichtige Effektorzellen der angeborenen Immunantwort, deren Entwicklung und Aktivierungswege attraktive therapeutische Ziele darstellen. Sie bestehen aus ILC der Gruppe 1 (Natürliche Killerzellen (NK) und ILC1), ILC2 und ILC3. Neben T-Zellen leisten ILCs einen entscheidenen Beitrag zu den Typ-1-, Typ-2- und Typ-3-Immunantworten. Die Entwicklung von ILCs beim Menschen wurde jedoch noch nicht systematisch untersucht, und frühere in vitro Untersuchungen stützten sich auf die Analyse einiger weniger Marker oder Zytokine, die für die Bestimmung der Identität der verschiedenen ILC-Linien suboptimal sind. Um diese Mängel zu beheben, stellen wir hier eine Plattform vor, die zuverlässig alle menschlichen ILC-Linien aus CD34+ CD45RA+ hämatopoetischen Vorläuferzellen, gewonnen aus Nabelschnurblut und Knochenmark, erzeugt. Mit einem systematischen Ansatz zeigt diese Arbeit, dass eine einzige Kulturbedingung nicht ausreicht, um alle ILC-Untergruppen zu generieren, sondern stattdessen bestimmte Kombinationen von Zytokinen und Notch-Signalen für die Entscheidung über das Schicksal der Linien wesentlich ist. Eine umfangreiche Analyse des Transkriptoms ergab, dass der Erwerb von CD161 robust eine globale ILC-Signatur identifiziert und in vitro ILCs von T-Zell-Signaturen trennt. Die Identität spezifischer in vitro generierter ILC-Linien (NK-Zellen und ILC1, ILC2 und ILC3) wurde durch Proteinexpression, funktionelle Assays und Transkriptomanalysen auf globaler sowie auf Einzelzellebene umfassend validiert. Diese in vitro erzeugten ILC-Linien rekapitulieren die Signaturen und Funktionen ihrer ex vivo isolierten ILC-Pendants. Des Weiteren, behandeln diese Daten die Einschränkungen der Unterscheidung von menschlichen NK Zellen und ILC1 sowohl in vitro als auch ex vivo an. Darüber hinaus löst diese Plattform gängige Probleme bei der Untersuchung menschlicher ILCs, wie z. B. unzureichende Zellzahlen oder die mangelnde Verfügbarkeit von Gewebeproben. Insgesamt stellt diese Arbeit eine Ressource dar, die nicht nur zur Klärung der Biologie und Differenzierung menschlicher ILCs beiträgt, sondern auch als wichtiges Instrument zur Untersuchung der Dysregulation von ILC-Funktionen dient, die bei verschiedenen entzündlichen Erkrankungen des Menschen eine Rolle spielen.Innate lymphoid cells (ILCs) are critical effectors of innate immunity and inflammation that consist of Group 1 ILCs (natural killer (NK) cells and ILC1), ILC2, and ILC3. As tissue resident lymphocytes, they play a crucial role type 1, type 2 and type 3 immune responses, respectively. Importantly, dysregulated ILC populations have been linked to the pathogenesis of a variety of chronic inflammatory diseases and thus represent attractive therapeutic targets with a potential for autologous cell therapies. However, human ILC generation has not been systematically explored, and previous in vitro investigations have relied on the analysis of few markers or cytokines, which are suboptimal to assign lineage identity and full functional capacity. To address these faults, we present here an effective in vitro platform, which reliably generates the core human ILC lineages from CD34+ CD45RA+ hematopoietic progenitors derived from cord blood and bone marrow. With a systematic approach, this work shows that a single culture condition is insufficient to generate all ILC subsets, and instead, distinct combinations of cytokines and Notch signaling are essential for lineage fate making decisions. In depth transcriptomic analysis revealed that acquisition of CD161 robustly identifies a global ILC signature and separates them from T cell signatures in vitro. The identity of specific ILC subsets, (NK cells and ILC1, ILC2, and ILC3) generated in vitro was validated extensively by protein expression, functional assays, and both global and single-cell transcriptome analysis. These in vitro generated ILC subsets recapitulate the signatures and functions of their ex vivo ILC counterparts. Finally, these data shed light on the limitations in untying the identity of human NK cells and ILC1 in vitro, similarly correlating to lineage identification difficulties ex vivo. Additionally, this platform tackles common problems in human ILC studies such as insufficient cell numbers and scarce availability of tissue samples. Altogether, this work presents a resource not only to aid in clarifying human ILC biology and differentiation, but also to serve as an important tool to study dysregulation of ILC functions, which have been implied in various inflammatory diseases in humans

Towards fully automated high-dimensional parameterized macromodeling

This paper presents a fully automated algorithm for the extraction of parameterized macromodels from frequency responses. The reference framework is based on a frequency-domain rational approximation combined with a parameter-space expansion into Gaussian Radial Basis Functions (RBF). An iterative least-squares fitting with positivity constraints is used to optimize model coefficients, with a guarantee of uniform stability over the parameter space. The main novel contribution of this work is a set of algorithms, supported by strong theoretical arguments with associated proofs, for the automated determination of all the hyper-parameters that define model orders, placement and width of RBFs. With respect to standard approaches, which tune these parameters using time-consuming tentative model extractions following a trial-and-error strategy, the presented technique allows much faster tuning of the model structure. The numerical results show that models with up to ten independent parameters are easily extracted in few minutes