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A Survey on Model Predictive Control of DFIGs in Wind Energy Conversion Systems

CSEE Journal of Power and Energy Systems 2024年第3期10卷 1085-1104页

作者： Shuo Yan Junyu Chen Minghao Wang Yongheng Yang Jose M.Rodriguez STEM College RMIT UniversityMelbourneAustralia Hong Kong Polytechnic University Hong KongChina State Key Laboratory of Internet of Things for Smart City(UM) Department of Electrical and Computer EngineeringUniversity of MacaoMacaoChina College of Electrical Engineering Zhejiang UniversityHangzhou 310027China Universidad San Sebastin Campus BellavistaSantiago de ChileCLSantiago de Chile 000000Chile IEEE

This paper presents a comprehensive study on the model predictive control(MPC)of doubly fed induction generators(DFIG)in wind energy conversion systems(WECS);in particular the MPC of the rotor side *** general principle of prevalent MPC strategies is discussed to introduce the theoretical framework in the first ***,mainstream and high-performance MPC methods of DFIGs have been identified as model predictive current control(MPCC),model predictive torque control(MPTC),and model predictive power control(MPPC).Starting from analyzing dynamic models,these MPC strategies are investigated in terms of operating principles and technical *** paper further investigates implementation of MPC strategies in unbalanced *** on the quantitative and qualitative analysis of several case studies,performance of various MPC schemes is compared and their special features are *** for designing MPC strategies of DFIGs in WECS are provided.

关键词： Doubly fed induction generator(DFIG) model predictive control(MPC) wind energy

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Experimental Validation of Dynamics for Air Cushion Vehicles

Experimental Validation of Dynamics for Air Cushion Vehicles

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OCEANS 2024 - Halifax, OCEANS 2024

作者： Sakri, Shivani Dim, Matthew Brizzolara, Stefano Virginia Polytechnic Institute and State University Department of Aerospace and Ocean Engineering BlacksburgVA United States Virginia Polytechnic Institute and State University Department of Electrical and Computer Engineering BlacksburgVA United States

ISBN: (纸本)9798331540081

The research study conducts experimental tests to validate the theoretical mathematical model of hovercraft dynamics. Static and dynamic tests have been conducted to understand vehicle response and cushion dynamics. The study allows us to use experimental data to calibrate the theoretical model to understand the vehicle and fluid physics better. © 2024 IEEE.

关键词： Air cushion vehicles

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Parasitic Capacitance Analysis of Integrated Transformers with Parallel Windings

Parasitic Capacitance Analysis of Integrated Transformers wi...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Yuan, Tianlong Jin, Feng Li, Qiang Virginia Polytechnic and State University Center for Power Electronics Systems Bradley Department of Electrical and Computer Engineering Blacksburg United States

ISBN: (纸本)9798350376067

The electric transportation market has experienced rapid growth in recent years, driven by increasing environmental concerns. Resonant converters play a crucial role in this sector due to their ability to provide isolation and regulation functions with high efficiency. A resonant inductance embedded transformer is a critical component of the LLC resonant converter, significantly influencing the power density of the entire system, particularly in high-power applications. To achieve higher power density, the operating frequency often exceeds hundreds of kilohertz. At such high frequencies, parasitic capacitance cannot be ignored, as it may cause electromagnetic interference (EMI) issues. In high-power applications, integrated transformers with parallel windings are commonly used, adding complexity to the system. Measuring the parasitic capacitance of these transformers becomes increasingly challenging. This paper presents various measurement methods for an integrated transformer with parallel windings in a 30 kW LLC resonant converter. The results obtained from different measurement techniques were consistent with each other and with simulation results, validating the accuracy of the methods employed. © 2024 IEEE.

关键词： Resonant converters

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Analysis and Comparison of Integrated Planar Transformers for CLLC Resonant Converters

Analysis and Comparison of Integrated Planar Transformers fo...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Yuan, Tianlong Jin, Feng Yu, Gibum Li, Qiang Virginia Polytechnic and State University Center for Power Electronics Systems Bradley Department of Electrical and Computer Engineering Blacksburg United States

ISBN: (纸本)9798350376067

The advancement of electric vehicles and green energy technologies necessitates on-board chargers (OBCs) with higher power density and reduced costs. Integrated planar magnetics emerge as a highly competitive option due to their superior power density and ease of manufacturing compared to traditional magnetic designs. However, detailed flux analysis, particularly the distribution on the plate, remains essential for evaluating various transformer structures. This paper presents a comprehensive comparison of different core structures for integrated transformers, validated through an 11-kW CLLC resonant converter prototype with a 98.4% peak efficiency and 420 W/inch3 power density. © 2024 IEEE.

关键词： Resonant converters

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VaeDiff-DocRE: End-to-end Data Augmentation Framework for Document-level Relation Extraction 31

VaeDiff-DocRE: End-to-end Data Augmentation Framework for Do...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Tran, Khai Phan Hua, Wen Li, Xue School of Electrical Engineering and Computer Science The University of Queensland Australia Department of Data Science and Artificial Intelligence The Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)9798891761964

Document-level Relation Extraction (DocRE) aims to identify relationships between entity pairs within a document. However, most existing methods assume a uniform label distribution, resulting in suboptimal performance on real-world, imbalanced datasets. To tackle this challenge, we propose a novel data augmentation approach using generative models to enhance data from the embedding space. Our method leverages the Variational Autoencoder (VAE) architecture to capture all relation-wise distributions formed by entity pair representations and augment data for underrepresented relations. To better capture the multi-label nature of DocRE, we parameterize the VAE's latent space with a Diffusion Model. Additionally, we introduce a hierarchical training framework to integrate the proposed VAE-based augmentation module into DocRE systems. Experiments on two benchmark datasets demonstrate that our method outperforms state-of-the-art models, effectively addressing the long-tail distribution problem in DocRE. Our code is released at: https://***/khaitran22/VaeDiff-DocRE. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Challenges and Opportunities in Healthcare and Industrial IoT: A Comparative Analysis 1

Challenges and Opportunities in Healthcare and Industrial Io...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Berjis, Zaid Ameen, Siddeeq Y. Al-Jammas, Mohammed H. Electrical and Computer Engineering Department College of Engineering University of Duhok Duhok Iraq Energy Engineering Department College of Technical Engineering Duhok Polytechnic University Duhok Iraq Computer and Information Engineering Department College of Electronics Ninevah University Mosul Iraq

ISBN: (纸本)9798331533557

The Internet of Things (IoT) has changed many industries by enabling smart devices to transmit data, operate autonomously, and interact in real-time. Among its most prominent applications are in healthcare and industrial sectors, where IoT is classified into two classes: massive Machine-Type Communication (mMTC) and Ultra-Reliable Low Latency Communication (URLLC). While mMTC devices prioritize low energy consumption and can handle large-scale deployments with minimal data rates, URLLC devices are focused on mission-critical applications requiring ultra-low latency and high reliability. This paper examines the challenges and opportunities of IoT implementation in healthcare and industrial sectors, focusing on interoperability, data security, and scalability issues. The objective is to provide actionable solutions for the effective integration of IoT technologies. The investigation shows that in healthcare, mMTC is utilized for non-critical monitoring, while URLLC supports critical tasks like remote surgery. In industrial settings, mMTC improves processes like supply chain management, while URLLC enables automation and real-time control of machinery. Despite these opportunities, challenges such as data privacy, security, interoperability, and reliability remain. Addressing these issues is crucial for unlocking the full potential of IoT in healthcare and industrial sectors. © 2024 IEEE.

关键词： Data privacy

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In-situ fabrication of vertical heterogeneous nickel diselenide-molybdenum diselenide architectures as bifunctional overall water-splitting electrocatalyst

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Journal of Materials Science & Technology 2024年第10期177卷 256-263页

作者： He Zhou Jingrui Hou Limin Zhang Dezhi Kong Hui Wang Longhui Zeng Zhiwei Ren Tingting Xu Ye Wang Key Laboratory of Material Physics Ministry of EducationSchool of Physics and MicroelectronicsZhengzhou UniversityZhengzhou 450001China Department of Electrical and Computer Engineering University of California at San DiegoSan DiegoCA 92093USA Department of Electronic and Information Engineering The Hong Kong Polytechnic UniversityHung HomKowloon 999077Hong KongChina

Despite the rapid advances in electrocatalysts based on two-dimensional(2D)transition metal dichalco-genides(TMDs)materials,they are subject to serious aggregation,poor conductivity and the presence of inactive basal ***,we have successfully demonstrated the in-situ construction of NiSe_(2)-MoSe_(2) heterostructure arrays on carbon cloth(NiSe_(2)-MoSe_(2)/CC)by a facile two-step hydrothermal *** presence of the synergistic effect in the heterostructures effectively optimizes the poor conductivity and hydrophilicity,and thus enables fast electron transfer,leading to enhanced electrochemical ***-thermore,density functional theory calculations reveal that the electrons redistribution at the heterojunc-tion interface and the reduced Gibbs free energy of hydrogen adsorption for hydrogen evolution reaction(HER)/the Gibbs free energy change value of rate-determining step for oxygen evolution reaction(OER),thus enhancing the HER/OER catalytic ***,the device displays a good performance with a low overpotential of 98 and 310 mV for HER and OER,respectively,and a low cell voltage of 1.59 V for its corresponding electrolyzer(10 mA cm^(-2)).This work presents the high-performance water splitting of bifunctional electrocatalysts based on 2D TMDs materials and offers a novel design concept of interface engineering.

关键词： Bifunctional electrocatalyst Heterostructures Hydrogen/oxygen evolution reaction Water splitting Synergistic effect

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OblivTime: Oblivious and Efficient Interval Skyline Query Processing Over Encrypted Time-Series Data

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IEEE Transactions on Services Computing 2025年第3期18卷 1602-1617页

作者： Ouyang, Huajie Zheng, Yifeng Wang, Songlei Hua, Zhongyun Harbin Institute of Technology School of Computer Science and Technology Guangdong Shenzhen518055 China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518055 China

Time-series data is prevalent in many applications like smart homes, smart grids, and healthcare. And it is now increasingly common to store and query time-series data in the cloud. Despite the benefits, data privacy concerns in such outsourced services are pressing, making it imperative to embed privacy assurance mechanisms from the outset. Most existing related works have been focused on querying for different types of aggregate statistics. In this paper, we instead focus on the secure support for advanced interval skyline queries, which allow to identify time series that are not dominated by any other time series within a query time interval. This is valuable for time-series data analytics in applications like remote health monitoring (e.g., identifying patients with high heart rates in a certain week). We present OblivTime, a new system framework for oblivious and efficient interval skyline query processing over encrypted time-series data. OblivTime is built from a synergy of time-series data analytics, lightweight cryptography, and GPU parallel computing, achieving stronger security guarantees and lower online query latency over the state-of-the-art prior work. Extensive experiments demonstrate that OblivTime can achieve up to 666\times speedup in online query latency over the state-of-the-art prior work. © 2008-2012 IEEE.

关键词： Structured Query Language

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Towards trustworthy multi-modal motion prediction:Holistic evaluation and interpretability of outputs

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 557-572页

作者： Sandra Carrasco Limeros Sylwia Majchrowska Joakim Johnander Christoffer Petersson MiguelÁngel Sotelo David Fernández Llorca Computer Engineering Department Polytechnic SchoolUniversity of AlcalaMadridSpain AI Sweden GothenburgSweden Zenseact AB GothenburgSweden Department of Electrical Engineering Linköping UniversityLinköpingSweden Chalmers University of Technology GothenburgSweden European Commission Joint Research CentreSevilleSpain

Predicting the motion of other road agents enables autonomous vehicles to perform safe and efficient path *** task is very complex,as the behaviour of road agents depends on many factors and the number of possible future trajectories can be consid-erable(multi-modal).Most prior approaches proposed to address multi-modal motion prediction are based on complex machine learning systems that have limited ***,the metrics used in current benchmarks do not evaluate all aspects of the problem,such as the diversity and admissibility of the *** authors aim to advance towards the design of trustworthy motion prediction systems,based on some of the re-quirements for the design of Trustworthy Artificial *** focus is on evaluation criteria,robustness,and interpretability of ***,the evaluation metrics are comprehensively analysed,the main gaps of current benchmarks are identified,and a new holistic evaluation framework is ***,a method for the assessment of spatial and temporal robustness is introduced by simulating noise in the perception *** enhance the interpretability of the outputs and generate more balanced results in the proposed evaluation framework,an intent prediction layer that can be attached to multi-modal motion prediction models is *** effectiveness of this approach is assessed through a survey that explores different elements in the visualisation of the multi-modal trajectories and *** proposed approach and findings make a significant contribution to the development of trustworthy motion prediction systems for autono-mous vehicles,advancing the field towards greater safety and reliability.

关键词： autonomous vehicles evaluation interpretability multi-modal motion prediction robustness trustworthy AI

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ANUBIS: Hybrid FPAA-FPGA Architecture for Entropy-Based True Random Number Generation in Secure UAV Communication

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IEEE Embedded Systems Letters 2024年第3期17卷 164-167页

作者： El-Hadedy, Mohamed Abelian, Andrea Lee, Kenny Cheng, Benny Hwu, Wen-Mei California State Polytechnic University Department of Electrical and Computer Engineering Pomona United States University of Illinois at Urbana-Champaign Coordinated Science Laboratory United States Naval Surface Warfare Center United States

Field-Programmable Gate Arrays (FPGAs) and Field-Programmable Analog Arrays (FPAAs) are reconfigurable circuits that enable flexible digital and analog implementations post-manufacturing. FPGAs are widely used in telecommunications, mixed-signal, and embedded systems due to their parallel processing and reconfigurability. Meanwhile, FPAAs provide flexibility for analog systems, which is crucial for modern mixed-signal processing. This study introduces ANUBIS, a hybrid system combining FPGA and FPAA technologies to generate true random numbers (TRNGs) for secure UAV communication. Due to its reliability and cost efficiency, ANUBIS leverages a thermistor circuit as an entropy source. The FPAA amplifies the analog noise generated by the thermistor, while the FPGA digitizes and processes the signal using Von Neumann Whitening (VNW) to remove bias. The ASCON hash function is applied to the whitened bitstream to generate cryptographically secure keys. These keys are utilized in a DHKE to enable secure communication via Bluetooth Low Energy (BLE), an ideal protocol for energy-constrained UAV applications. ANUBIS demonstrates reconfigurability, power efficiency, and ease of implementation, showcasing its potential for secure communication applications. It achieves robust randomization, setting a new standard for UAV communication security and addressing applications requiring reliable TRNG solutions. The system consumes 1.615 W in total, with 1.54 W consumed by the FPGA and 75 mW by the FPAA. Resource utilization on the PYNQ-Z1 board includes 5,186 LUTs (9.75%), 549 units of memory (3.15%), and 5.5 units of BRAM (3.93%), indicating moderate resource usage with room for future enhancements. By integrating reliable analog noise harvesting with efficient digital post-processing, ANUBIS offers a novel approach to TRNG design, demonstrating the potential for broader cryptographic applications in resource-constrained environments. © 2009-2012 IEEE.

关键词： Random number generation

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