323,537 research outputs found
Sensorless Speed Control of Synchronous Reluctance Motor Drives Based on Extended Kalman Filter and Neural Magnetic Model
No full textDue to their robustness and adaptability, position estimators based on the extended Kalman filter have been used in permanent magnet synchronous motors for decades. The time has come to extend their use to reluctance motors as well and this work focuses on the elements that hinder the transition. All passes through the availability of an accurate and analytical magnetic model, which is obtained by Artificial Intelligence tools. It is proved that the sensorless control of synchronous reluctance motors using the extended Kalman filter is possible over broad speed and torque ranges. The experimental session compares different implementation possibilities, concluding with the proposal of a new hybrid algorithm that greatly reduces the computational load
Enriched Pitman–Yor processes
No full textBayesian non-parametrics has evolved into a broad area encompassing flexible methods for Bayesian inference, combinatorial structures, tools for complex data reduction, and more. Discrete prior laws play an important role in these developments, and various choices are available nowadays. However, many existing priors, such as the Dirichlet process, have limitations if data require nested clustering structures. Thus, we introduce a discrete non-parametric prior, termed the enriched Pitman–Yor process, which offers higher flexibility in modeling such elaborate partition structures. We investigate the theoretical properties of this novel prior and establish its formal connection with the enriched Dirichlet process and normalized random measures. Additionally, we present a square-breaking representation and derive closed-form expressions for the posterior law and associated urn schemes. Furthermore, we demonstrate that several established models, including Dirichlet processes with a spike-and-slab base measure and mixture of mixtures models, emerge as special instances of the enriched Pitman–Yor process, which therefore serves as a unified probabilistic framework for various Bayesian non-parametric priors. To illustrate its practical utility, we employ the enriched Pitman–Yor process for a species-sampling ecological problem
Partial melting of carbonatic ultracataclasites due to seismic faulting (Southern Grigna, Central Alps, Italy)
No full textPartial melting of carbonatic ultracataclasites due to seismic faulting (Southern Grigna, Central Alps, Italy),
No full textDiffusive author(s), cohesive author: Analysis of S/N (1994)
No full textThis study indicates the ways in which various aspects of the author(s) are brought forth in Dumb type’s performance art, the S/N production. Previous research has suggested a non-hierarchical organization of Dumb type and the absence of a “privileged author” in Dumb type’s collaborative work, S/N. However, the results that I have investigated from member’s interviews on the creative process of S/N along with my analysis of the recorded images of S/N, indicate a different aspect of the author(s). First, S/N was created through, so to speak, the collective ideas of the members of Dumb type. Further, S/N has at least nine quotations from previous performances, installations, and printed writings, besides the work-in-progress technique. Explicating one of the “author functions” as given by Michel Foucault, each text has plural subjects of the author. However, it has been revealed from members’ interviews that Teiji Furuhashi had a decision-making role in selecting the members’ ideas within the performance. Since then, S/N has had plural subjects of creation; however, Furuhashi is one of the subjects of creation along with the “privileged author.” S/N has plural authors (diffusive authors) yet at the same time, it has a “privileged author,” Teiji Furuhashi (cohesive author)
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
ENHANCING GEOMETRIC EDGE DETAILS IN MVS RECONSTRUCTION
No full textMesh models generated by multi view stereo (MVS) algorithms often fail to represent in an adequate manner the sharp, natural edge details of the scene. The harsh depth discontinuities of edge regions are eventually a challenging task for dense reconstruction, while vertex displacement during mesh refinement frequently leads to smoothed edges that do not coincide with the fine details of the scene. Meanwhile, 3D edges have been used for scene representation, particularly man-made built environments, which are dominated by regular planar and linear structures. Indeed, 3D edge detection and matching are commonly exploited either to constrain camera pose estimation, or to generate an abstract representation of the most salient parts of the scene, and even to support mesh reconstruction. In this work, we attempt to jointly use 3D edge extraction and MVS mesh generation to promote edge detail preservation in the final result. Salient 3D edges of the scene are reconstructed with state-of-the-art algorithms and integrated in the dense point cloud to be further used in order to support the mesh triangulation step. Experimental results on benchmark dataset sequences using metric and appearance-based measures are performed in order to evaluate our hypothesis
Surface reconstruction assessment in photogrammetric applications
No full textThe image-based 3D reconstruction pipeline aims to generate complete digital representations of the recorded scene, often in the form of 3D surfaces. These surfaces or mesh models are required to be highly detailed as well as accurate enough, especially for metric applications. Surface generation can be considered as a problem integrated in the complete 3D reconstruction workflow and thus visibility information (pixel similarity and image orientation) is leveraged in the meshing procedure contributing to an optimal photo-consistent mesh. Other methods tackle the problem as an independent and subsequent step, generating a mesh model starting from a dense 3D point cloud or even using depth maps, discarding input image information. Out of the vast number of approaches for 3D surface generation, in this study, we considered three state of the art methods. Experiments were performed on benchmark and proprietary datasets of varying nature, scale, shape, image resolution and network designs. Several evaluation metrics were introduced and considered to present qualitative and quantitative assessment of the results
Comparison Between UKF and EKF in Sensorless Synchronous Reluctance Motor Drives
No full textThe reduction of the human environmental footprint can be achieved through the use of more efficient motors, such as synchronous reluctance motors (SynRMs). Known for their affordability, SynRMs are increasingly employed in sensorless AC drives. This paper presents a critical comparison of sensorless algorithms based on two nonlinear Kalman Filters (Unscented and Extended). The objective is to highlight the theoretical and practical advantages and drawbacks of each method when applied to the speed control of a SynRM, culminating in a definitive decision on the best choice. The magnetic model of the SynRM is much more nonlinear than that of induction motors, which are predominantly addressed in existing literature. This study aims to fill the gap by answering the question: “Is the extended Kalman filter still the best choice even in the case of nonlinear electric motors?” The answer comes through a large batch of experiments, including speed and load torque tests, zero-speed standstill starts, parameter sensitivity, and evaluation of computational burdens for both Kalman filter algorithms
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