1,720,956 research outputs found
FAULT-TOLERANT GRID SYNCHRONIZATION OF THREE-PHASE PWM RECTIFIERS USING NEURAL NETWORK
No full textThis work focuses on the essential role of synchronous angle estimation in the conversion of three-phase AC to DC voltage. Accurately determining the synchronous angle is crucial for achieving optimal phasing in the abc/d-q transformation, aligning the synchronous reference d-q with the phase “a” voltage vector. This alignment ensures the efficient operation of the inner current loops in the d-q synchronous reference. However, estimating the synchronous angle becomes challenging during AC grid faults. Previous studies have employed phase-locked loops (PLLs) with specialized filters to handle parasitic harmonics. In contrast, this research proposes using neural networks to recognize fault types and estimate the phase with minimal perturbations. Comparative analyses of conventional PLL-based and neural network-based estimates of the converter bridge's output performance under fault conditions are presented using MATLAB/Simulink/PLECS
Rapid Control Prototyping of Synchronous Reluctance Motor Drives by Matlab/Simulink
No full textThis paper concerns the rapid control prototyping of electrical drives. Off-line and real-time identical target simulations are presented, based on a Texas Instruments Delfino F28379S micro-controller. A synchronous reluctance motor drive is considered, accounting for the electromagnetic nonlinearities of the machine. In offline prototyping, the controlled hardware (motor, converter, and transducers) is modeled in Simulink, whereas in real-time prototyping, it is simulated directly on the micro-controller hardware by proper models. Then, both the approaches share the same control algorithm but run on different platforms, thus providing different prototyping features. Exemplary experiments complete the study. In particular, experimental validation of real-time simulation of the SynRel is not reported in the literature to date
Neural Network Control of AC/DC Converters Robust to AC Grid Faults
No full textThis work presents the experimental application of artificial neural networks to improve the control of grid-connected AC/DC converters. The challenging context of AC grid faults is addressed and a general-purpose three-phase PWM rectifier equipped with IGBT technology, operating at 10 kHz switching frequency, is considered. A power supply facility with grid simulation capability emulates the most common failures. The estimation of the grid angle, critical for the efficient control in the synchronous d-q reference frame, is achieved by a set of neural networks depending on the type of fault, also identified by neural networks. The MATLAB/Simulink environment trains and simulates the neural networks and builds the control code for the target Texas Instruments Delfino F28379S microcontroller. The consolidated quadrature phase-locked-loop approach for grid synchronization is considered for comparison. The results demonstrate superior reliability when neural networks are used, especially when grid faults occur
High Accuracy Real-Time Simulation of Synchronous Reluctance Motor Drive Using Parallel Processing
No full textThis paper presents a parallel processing approach to the real-time simulation of electrical drives. In a real-time simulation, the plant model runs on the same target controller and at the same control rate as the actual application. Hence, the plant model must be as accurate and the integration step of its solver as small as possible. The computing capabilities of the Texas Instruments Delfino F28379S microcontroller, specifically the availability of the Control Law Accelerator coprocessor, are explored using MATLAB/Simulink. A synchronous reluctance motor drive, challenging due to intrinsic nonlinearities and fast transients, is considered. The subdivision of control and plant modeling tasks between the Central Processing Units and the Control Law Accelerator and their synchronization issues are presented and discussed. For a better evaluation, different solver algorithms are analyzed. A detailed comparison between experimental tests and real-time simulations completes the work
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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