CNR Institute of Intelligent Systems for Automation

Palermo, Italy

CNR Institute of Intelligent Systems for Automation

Palermo, Italy
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Anglani R.,CNR Institute of Intelligent Systems for Automation | Casalbuoni R.,University of Florence | Ciminale M.,dellUniversita e della Ricerca | Ippolito N.,National Institute of Nuclear Physics, Italy | And 3 more authors.
Reviews of Modern Physics | Year: 2014

Inhomogeneous superconductors and inhomogeneous superfluids appear in a variety of contexts including quark matter at extreme densities, fermionic systems of cold atoms, type-II cuprates, and organic superconductors. In the present review the focus is on properties of quark matter at high baryonic density, which may exist in the interior of compact stars. The conditions realized in these stellar objects tend to disfavor standard symmetric BCS pairing and may favor an inhomogeneous color superconducting phase. The properties of inhomogeneous color superconductors are discussed in detail and in particular of crystalline color superconductors. The possible astrophysical signatures associated with the presence of crystalline color superconducting phases within the core of compact stars are also reviewed. © 2014 American Physical Society.


Accetta A.,University of Palermo | Cirrincione M.,University of Technology of Belfort - Montbéliard | Pucci M.,CNR Institute of Intelligent Systems for Automation | Vitale G.,CNR Institute of Intelligent Systems for Automation
IEEE Transactions on Industrial Electronics | Year: 2012

This paper presents a sensorless technique for permanent-magnet synchronous motors (PMSMs) based on high-frequency pulsating voltage injection. Starting from a speed estimation scheme well known in the literature, this paper proposes the adoption of a neural network (NN) based adaptive variable-band filter instead of a fixed-bandwidth filter, needed for catching the speed information from the sidebands of the stator current. The proposed NN filter is based on a linear NN adaptive linear neuron (ADALINE), trained with a classic least mean squares (LMS) algorithm, and is twice adaptive. From one side, it is adaptive in the sense that its weights are adapted online recursively. From another side, its bandwidth is made adaptive during the running of the drive, acting directly on the learning rate of the NN filter itself. The immediate consequence of adopting a variable-band structure is the possibility to enlarge significantly the working speed range of the sensorless drive, which can be increased by a factor of five. The proposed observer has been tested experimentally on a fractional horsepower PMSM drive and has been compared also with a fixed-bandwidth structure. © 2011 IEEE.


Pucci M.,CNR Institute of Intelligent Systems for Automation | Cirrincione M.,CNR Institute of Intelligent Systems for Automation | Cirrincione M.,University of Technology of Belfort - Montbéliard
IEEE Transactions on Industrial Electronics | Year: 2011

This paper presents a maximum power point tracking (MPPT) technique for high-performance wind generators with induction machines based on the growing neural gas (GNG) network. In this paper, a GNG network has been trained offline to learn the turbine-characteristic surface torque versus wind and machine speeds and has been implemented online to obtain the wind tangential speed on the basis of the estimated torque and measured machine speed (surface function inversion). The machine reference speed is then computed on the basis of the optimal tip speed ratio. For the experimental application, a back-to-back configuration with two voltage source converters has been considered, one on the machine side and the other on the grid side. The field-oriented control of the machine has been further integrated with an intelligent sensorless technique; in particular, the so-called total least squares (TLS) EXIN full-order observer has been adopted. Finally, a comparison with a classic perturb-and-observe MPPT has been made on a real wind-speed profile. © 2006 IEEE.


Bartolini G.,University of Cagliari | Punta E.,CNR Institute of Intelligent Systems for Automation
IEEE Transactions on Automatic Control | Year: 2010

The note considers the variable-structure control of nonlinear known nonaffine systems when the state vector is not completely available and the use of observers is required. The strategy of introducing integrators in the input channel is exploited to enlarge the class of tractable control systems. A new reduced-order observer is proposed and conditions are found under which it is proven the convergence to the unique ideal solution of both system and observer. The control problem is solved by forcing a sliding regime for the observer, while satisfying an exponential stability criterion for the observation error state equation. © 2010 IEEE.


Wasowski J.,CNR Research Institute for Geo-hydrological Protection | Bovenga F.,CNR Institute of Intelligent Systems for Automation
Engineering Geology | Year: 2014

Multi Temporal Interferometry (MTI) stands for advanced synthetic aperture radar differential interferometry (DInSAR) techniques, which include Permanent/Persistent Scatterers Interferometry - PSInSAR™/PSI and similar methods, as well as Small Baseline Subset - SBAS and related/hybrid approaches. These techniques are capable to provide wide-area coverage (thousands of km2) and precise (mm-cm resolution), spatially dense information (from hundreds to thousands of measurement points/km2) on ground surface deformations. New MTI application opportunities are emerging thanks to i) greater data availability from radar satellites, and ii) improved capabilities of the new space radar sensors (X-band Cosmo-SkyMed, C-band RADARSAT-2, TerraSAR-X) in terms of resolution (from 3 to 1m) and revisit time (from 11 to 4days for X-band acquisitions). This implies greater quantity and quality information about ground surface displacements and hence improved landslide detection and monitoring capabilities. Even though the applicability of MTI to regional and local-scale investigations of slow landslides has already been demonstrated, the awareness of the MTI utility and its technical limitations among landslide scientists and practitioners is still rather low. By referring to recent works on radar remote sensing, many regional and local scale MTI application examples from the geoscience literature and our own studies, we present an up-to-date overview of current opportunities and challenges in this field. We discuss relevant technical constraints and data interpretation issues that hamper the use of MTI in landslide assessment. Then guidelines on how to mitigate MTI technical limitations and avoid erroneous interpretations of radar-derived slope surface deformations are presented for the benefit of users lacking advanced knowledge in SAR applications. Finally, in view of the upcoming radar satellite launches, future perspectives on MTI applications are outlined and recommendations for applied research priorities are suggested. We foresee that with regular globe-scale coverage, improved temporal resolution (weekly or better) and freely available imagery, new radar satellite background missions such as the European Space Agency's Sentinel-1 will guarantee ever increasing and more efficient use of MTI in landslide investigations. Furthermore, thanks to the improved temporal and spatial resolutions of the new generation radar sensors, significant breakthroughs are expected in detailed slope instability process modeling (e.g. kinematic and geotechnical models), as well as in the understanding of spatial and temporal patterns of landslide movement/activity and their relationships to causative or triggering factors (e.g. precipitation, seismic loading). © 2014 Elsevier B.V.


Mattia F.,CNR Institute of Intelligent Systems for Automation
Waves in Random and Complex Media | Year: 2011

A recent experimental study by Wegmuller et al. has reported on directional backscattering patterns in the Synthetic Aperture Radar (SAR) response of bare or sparsely vegetated agricultural soils that require a better understanding of scattering from tilled soils. Shin and Kong modeled the latter as quasi-periodic rough surfaces and showed that the total backscatter consists of three terms, one due to the coherent field and the other two arising from the incoherent scattered field. However, all the simulations reported by Shin and Kong are only concerned with one of the terms contributing to the incoherent scattering and could not predict highly directional backscattering patterns. In this context, the objective of this work is: (1) to extend the Shin-Kong model in order to compute in a finite form all the coherent and incoherent terms; (2) to describe the case of quasi-periodic rough surfaces having quasi-parallel row directions. Results indicate that the new model can predict very narrow (i.e. a few tenths of a degree angular aperture) backscatter peaks when the wave incidence plane is quasi-orthogonal to the row tillage direction. More generally, the paper's results point to the importance of anisotropic tillage patterns in modulating the radar backscatter in the entire azimuthal plane. © 2011 Taylor & Francis.


Cervellera C.,CNR Institute of Intelligent Systems for Automation
IEEE Transactions on Neural Networks | Year: 2010

In this brief, the use of lattice point sets (LPSs) is investigated in the context of general learning problems (including function estimation and dynamic optimization), in the case where the classic empirical risk minimization (ERM) principle is considered and there is freedom to choose the sampling points of the input space. Here it is proved that convergence of the ERM principle is guaranteed when LPSs are employed as training sets for the learning procedure, yielding up to a superlinear convergence rate under some regularity hypotheses on the involved functions. Preliminary simulation results are also provided. © 2006 IEEE.


Caviglione L.,CNR Institute of Intelligent Systems for Automation
Proceedings - 2011 4th IEEE International Conference on Utility and Cloud Computing, UCC 2011 | Year: 2011

Owing to an explosive growth, Web 2.0 technologies are now widespread. Moreover, they have been increasingly mixed with the cloud model to produce highly sophisticated services, also with an increased social flavor. In this perspective, Social Networks (SNs) are a paradigmatic example, allowing to share user-generated contents, while assuring a high degree of interactivity. Such facets introduce new usage patterns reflecting in new features in the produced HTTP traffic. Therefore, additional modeling is needed, since standard HTTP behaviors could not easily capture new trends. This paper introduces an extension to standard HTTP behavioral models, by considering new elements generated by SN applications. To prove the correctness of the proposed approach, a traffic characterization of one of the most popular SN is presented. © 2011 IEEE.


Di Piazza M.C.,CNR Institute of Intelligent Systems for Automation | Vitale G.,CNR Institute of Intelligent Systems for Automation
Applied Energy | Year: 2010

In this paper the development of a new laboratory prototype for the emulation of a photovoltaic (PV) field is presented. The proposed system is based on a DC/DC step-down converter topology and allows to obtain the solar array I-V curves, taking into account the environmental changes in solar irradiance and cell temperature. The DC/DC converter control strategy is deduced by using a comprehensive mathematical model of the PV field whose parameters are obtained from the knowledge of: (a) maximum power point data, measured when the PV plant power converter is running, (b) open circuit voltage and short-circuit current, measured off-line. This approach allows the most accurate representation of the PV source. Computer simulations and experimental results demonstrate that the proposed circuit acts as a highly accurate and efficient laboratory simulator of the photovoltaic array electrical characteristics both in steady state and transient conditions. Partial shading and fluctuating conditions can be reproduced too. Moreover the dynamic behaviour of the proposed laboratory emulator is suitable to its effective connection to power electronic interface to the utility or to load through a DC/DC boost converter. © 2009 Elsevier Ltd. All rights reserved.


Pucci M.,CNR Institute of Intelligent Systems for Automation
Electric Power Systems Research | Year: 2012

This paper deals with direct field oriented control of linear induction motor drives. After elaborating the inductor and induced part space-vector equations of the LIM in several reference frames, some induced part flux models taking into consideration the end effects are presented. In particular, the so called "voltage model" based on the inductor equations in the inductor reference frame and the "current model" based on induced part equations in both the inductor and induced part flux linkage reference frames are deduced and compared to the rotational induction machine counterpart. Afterwards, after a proper tuning of such models based on both FEA (finite element analysis) and experimental measurements, some simulation and experimental tests have been performed. Simulations show that the proposed flux models taking into consideration the LIM end effects permit the drive to achieve better dynamic performance. Moreover, some comparative experimental results, adopting both the current and the voltage flux models, have been performed on a suitably devised test set-up. © 2012 Elsevier B.V. All rights reserved.

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