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International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Ryo Takahashi Kazuki Abe Hiroshi Takami Fuminori Ishibashi Graduate School of Electrical Eng. and Computer Science Shibaura Institute of Technology Tokyo Japan Dept. of Electrical Eng. and Robotics Course College of Engineering Shibaura Institute of Technology Tokyo Japan Dept. of Electrical Eng. Faculty of Eng. Shibaura Institute of Technology Tokyo Japan

ISBN: (数字)9798350375589

ISBN: (纸本)9798350375596

This paper proposes a novel grid-connected inverter with LCL filters applied to IRM-ILQ (Inverse Reference Model - Inverse Linear Quadratic) control strategy. The IRM, which is feed-forward control, allows for realizing the fast response to current control without delay. The ILQ control gives an analytical solution for optimal control, and response speed in the closed-loop system is controlled. The IRM-ILQ control method simultaneously provides target tracking and error convergence, basically the IRM-ILQ control is the two-degree of freedom control. Owing to it, it can suppress surge current less than 58.6% during momentary power failure and make power factor keep unity even when command current value changes. The proposed grid-connected inverter is confirmed current tracking and an impressive adaptability to varying amplitude and phase of current by numerical simulations.

关键词： Current control Transient response Renewable energy sources Reactive power Filters Target tracking Numerical simulation Inverters Proposals Surges

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A Proposal of Speed Sensorless Control Based on IRM-ILQ Control for SPMSM Drive with Active LC Filter

A Proposal of Speed Sensorless Control Based on IRM-ILQ Cont...

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International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Ryoki Mikami Kazuki Abe Hiroshi Takami Fuminori Ishibashi Graduate School of Electrical Eng. And Computer Science Shibaura Institute of Technology Koto-ku Tokyo Japan Dept. of Electrical Eng. and Robotics Course College of Engineering Shibaura Institute of Technology Koto-ku Tokyo Japan Dept. of Electrical Eng. Faculty of Eng. Shibaura Institute of Technology Koto-ku Tokyo Japan

ISBN: (数字)9798350375589

ISBN: (纸本)9798350375596

Generally, a position detector has been used to drive the Surface Permanent Magnet Synchronous Motor (SPMSM), because the current and voltage must be controlled according to the magnetic pole position of the rotor. However, using a position detector causes problems such as more expensive and lower reliability due to position detector failure. Therefore, the speed sensor-less control, which estimates the magnetic pole position from voltage and current without using a position detector, is required. Harmonic components in the output voltage waveform of the PWM inverter used to drive the SPMSM can cause problems such as Electromagnetic Interference (EMI). Harmonic components can be suppressed by using an LC filter. In addition, IRM-ILQ control, which combines modern control theory's Inverse Linear Quadratic (ILQ) control and Inverse Reference Model (IRM), can achieve stable and robust SPMSM drive despite with LC filter. In this paper, robustness of speed sensorless control based on IRM-ILQ current control for SPMSM with active LC filter is described. In simulation, the proposed method allows stable control even when there are parameter errors.

关键词： Maximum likelihood detection Magnetic separation Electromagnetic interference Sensorless control Detectors Nonlinear filters Drives Harmonic analysis Voltage control Power harmonic filters

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A Clarke-Wavelet-Based Time-Domain Power Transformer Differential Protection

A Clarke-Wavelet-Based Time-Domain Power Transformer Differe...

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IEEE General Meeting Power& Energy Society

作者： Rodrigo Medeiros Flavio Costa Kleber Silva Jose Chavez Jose Lima Junior Marjan Popov Multidisciplinary Center of Caraubas Federal Rural University of the Semi-Arid School of Science and Technology Federal University of Rio Grande do Norte Department of Electrical Engineering University of Brasilia Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Electrotechnical Engineering Course University of Pernambuco

ISBN: (数字)9781665408233

ISBN: (纸本)9781665408240

Phasor-based differential protection is widely used as the main protection function of the power transformer due to its reliability and ability to discriminate internal from external faults and inrush currents. However, these methods present some delays due to phasor convergence during the fault occurrence and can fail during challenging situations, such as transformer energizations with low second-harmonic content and turn-to-turn and turn-to-ground internal faults. This paper proposes a novel time-domain power transformer differential protection based on Clarke and wavelet transforms with only one differential unit and with automatic setting to be used in any power transformer. Considering both actual and simulation data, the performance validation reveals that the proposed method is efficient, ultra-fast, simple, and independent of the fundamental and harmonic components of the differential current. The method was also implemented in a real-time digital simulator to demonstrate its practical feasibility.

关键词： Wavelet transforms Surge protection Harmonic analysis Frequency conversion Real-time systems Delays Power transformers

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Development of an Efficient Charging Control System for Pico-Hydro Power Generation Utilizing Multiple Impact Water Wheel (MIWW) with MPPT Control

Development of an Efficient Charging Control System for Pico...

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International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Yusuke Asami Hiroshi Takami Fuminori Ishibashi Shota Kawate Hidemi Kurita Masaki Shimizu Graduate School of Electrical Eng. and Computer Science Shibaura Institute of Technology Tokyo Japan Dept. of Electrical Eng. and Robotics Course College of Engineering Shibaura Institute of Technology Tokyo Japan Dept. of Electrical Eng. Faculty of Engineering Shibaura Institute of Technology Tokyo Japan Koa Electronics Co. Ltd. Nagano Japan Harmony with Nature Technology Laboratory Nagano Japan Souken Group Nagano Japan

ISBN: (数字)9798350375589

ISBN: (纸本)9798350375596

This paper introduces an advanced charging control system for a Multiple Impact Water Wheel (MIWW) used in pico-hydropower generation. The control system maximizes energy conversion efficiency by employing a Maximum Power Point Tracking (MPPT) algorithm, which dynamically adjusts the system's operation based on real-time voltage and current measurements. Unlike traditional methods that rely on monitoring rotational speed, this approach simplifies the system by eliminating the need for speed sensors, thereby reducing costs and enhancing reliability. The control system is structured into four main operational phases: the water turbine acceleration phase, optimal control (MPPT) phase, drooping characteristic suppression phase, and overvoltage protection phase. Each phase is designed to optimize distinct aspects of system performance, ensuring stable and efficient power generation under varying water flow conditions. Experimental validation was conducted by subjecting the system to three different water pressure levels (0.036 MPa, 0.048 MPa, and 0.042 MPa). The results demonstrate that the system successfully maintained stable voltage and current, even during rapid fluctuations in water pressure, confirming the effectiveness of the proposed MPPT algorithm. By addressing the challenges of droop characteristics and overvoltage conditions, the control system ensures the reliability and efficiency of pico-hydropower systems. This research contributes to the development of cost-effective, efficient, and sustainable energy solutions, especially in regions lacking conventional power infrastructure.

关键词： Maximum power point trackers Water Fluctuations Heuristic algorithms Velocity control Wheels Sensor systems Voltage control Power generation Turbines

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Harmonics Analysis and Evaluation for Active LC-LPF Attached PMSM Drive by IRM-ILQ Control Through Experiments

Harmonics Analysis and Evaluation for Active LC-LPF Attached...

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International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Kazuki Abe Yoshiki Sasaki Hiroshi Takami Fuminori Ishibashi Koji Shibasaki Maruwa Takumi Ebara Graduate School of Electrical Eng. and Computer Science Shibaura Institute of Technology Koto-ku Tokyo Japan Dept. of Electrical Eng. and Robotics Course College of Engineering Shibaura Institute of Technology Koto-ku Tokyo Japan Dept. of Electrical Eng. Faculty of Engineering Shibaura Institute of Technology Koto-ku Tokyo Japan Electronic Inc. Kashiwa-shi Chiba Japan Maruwa Electronic Inc. Kashiwa-shi Chiba Japan

ISBN: (数字)9798350375589

ISBN: (纸本)9798350375596

This paper describes analysis and evaluation of harmonics reduction for Active LC Low Pass Filter (LC-LPF) attached Surface Permanent Magnet Synchronous Motor (SPMSM) drive operated by IRM-ILQ (Inverse Reference Model - Inverse Linear Quadratic) current control. Harmonics due to high-speed switching of inverter should be reduced since it brings not only low efficiency motor drive such as torque ripple, also cause electromagnetic interference (EMI) problems. Those problems will be solved by appending LC-LPF though, LC resonant phenomena against inverter's carrier frequency and motor's operating frequency should be considered. The IRM-ILQ control is classified into modern control methods and simultaneously transacts multiple variables. Owing to it, stable motor drive can be realized even though LC-LPF is attached. In experiments, degrees of the harmonics reduction by Active LC-LPF are evaluated via Fast Fourier Transform (FFT) analysis and Total Harmonic Distortion (THD) and confirmed 2 % of voltage distortion on average in rated speed region.

关键词： Current control Motor drives Total harmonic distortion Fast Fourier transforms Electromagnetic interference Switches Harmonic analysis Distortion Voltage control Power harmonic filters

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Measurement of Absorption Current of Polyester Coated Enameled Wires with Q(t) Meter

Measurement of Absorption Current of Polyester Coated Enamel...

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International Symposium on electrical Insulating Materials

作者： Akinao Watanabe Masumi Fukuma Yoitsu Sekiguchi Advanced Electronic and Information Systems Course National Institute of Technology Matsue College Matsue Japan Department of Electrical Engineering and Computer Science National Institute of Technology Matsue College Matsue Japan Energy and Electronics Materials R&D Laboratories Sumitomo Electric Industries Osaka Japan

A Q(t) meter is used to measure electrical properties in insulating materials. Here, Q(t) is the integral value of circuit current with time t. It is possible to measure the Q(t) of the insulation material of a capacitor and a cable by using Q(t) meter. The current through an insulating material is divided into an instantaneous charging current, an absorption current and an equilibrium leakage current. It is considered that the absorption current is related to charge accumulation in the insulating materials. In this paper, an enameled wire (1.6 PEW) is used to prepare a cable sample, the Q(t) of the coated polyester (PEs) is measured, and extraction of absorption current components from measured Q(t) are reported.

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Artificial intelligence in multimodal learning analytics: A systematic literature review

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computers and Education: Artificial Intelligence 2025年 8卷

作者： Mohammadi, Mehrnoush Tajik, Elham Martinez-Maldonado, Roberto Sadiq, Shazia Tomaszewski, Wojtek Khosravi, Hassan School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia Department of Educational Psychology and Learning Systems Florida State University Tallahassee United States Centre for Learning Analytics at Monash Faculty of Information Technology Monash University Melbourne Australia Australian Research Council Centre of Excellence for Children and Families Over the Life Course The University of Queensland Brisbane Australia Institute for Social Science Research The University of Queensland Brisbane Australia Institute for Teaching and Learning Innovation The University of Queensland Brisbane Australia

The proliferation of educational technologies has generated unprecedented volumes of diverse, multimodal learner data, offering rich insights into learning processes and outcomes. However, leveraging this complex, multimodal data requires advanced analytical methods. While Multimodal Learning Analytics (MMLA) offers promise for exploring this data, the potential of Artificial Intelligence (AI) to enhance MMLA remains largely unexplored. This paper bridges these two evolving domains by conducting the first systematic literature review at the intersection of AI and MMLA, analyzing 43 peer-reviewed papers from 11 reputable databases published between 2019 and 2024. The findings indicate a growing trend in AI-enhanced MMLA studies published predominantly in high-quality venues, led by education researchers with a predominant focus on tertiary education targeting diverse stakeholders. Guided by a novel conceptual framework, our analysis highlights the transformative role of AI across the MMLA process, particularly in model learning and feature engineering. However, it also uncovers significant gaps, including limited AI implementation in components requiring deep integration with learning theories, insufficient application of advanced AI techniques, and lack of large-scale studies in authentic learning environments. The review identifies key benefits, such as enhanced personalization and real-time feedback, while also addressing challenges related to ethical considerations, data integration, and scalability. Our study contributes by offering comprehensive recommendations for future research, emphasizing international collaboration, multi-level studies, and ethical AI implementation. These findings advance the theoretical understanding of AI's role in education, providing a foundation for developing sophisticated, interpretable, and scalable AI-enhanced MMLA approaches, potentially revolutionizing personalized learning across diverse educational settings. © 2025

关键词： Educational robots

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NO FORMATION OF A NEW PHASE FOR A FREE BOUNDARY PROBLEM IN COMBUSTION THEORY

arXiv

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arXiv 2024年

作者： Furukawa, Ken Giga, Yoshikazu Kajiwara, Naoto Faculty of Science Academic Assembly University of Toyama 3190 Gofuku Toyama-shi Toyama930-8555 Japan Graduate School of Mathematical Sciences The University of Tokyo 3-8-1 Komaba Meguro-ku Tokyo153-8914 Japan Applied Physics Course Department of Electrical Electronic and Computer Engineering Gifu University 1-1 Yanagido Gifu501-1193 Japan

We consider a free boundary problem for the heat equation with a given non-negative external heat source. On the free boundary, we impose the zero Dirichlet condition and the fixed normal derivative so that heat escapes from the boundary. In various settings, we show that there exist no solutions when the initial temperature equals the fixed temperature no matter where the initial location of the free boundary is given provided that the external heat source is bounded from above. We also note that there is a chance to have a solution when the external temperature is unbounded as time tends to zero by giving a self-similar solution. Copyright © 2024, The Authors. All rights reserved.

关键词： Laplace transforms

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Towards deployment-centric multimodal AI beyond vision and language

arXiv

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arXiv 2025年

作者： Liu, Xianyuan Zhang, Jiayang Zhou, Shuo van der Plas, Thijs L. Vijayaraghavan, Avish Grishina, Anastasiia Zhuang, Mengdie Schofield, Daniel Tomlinson, Christopher Wang, Yuhan Li, Ruizhe van Zeeland, Louisa Tabakhi, Sina Demeocq, Cyndie Li, Xiang Das, Arunav Timmerman, Orlando Baldwin-McDonald, Thomas Wu, Jinge Bai, Peizhen Al Sahili, Zahraa Alwazzan, Omnia Do, Thao N. Suvon, Mohammod N.I. Wang, Angeline Cipolina-Kun, Lucia Moretti, Luigi A. Farndale, Lucas Jain, Nitisha Efremova, Natalia Ge, Yan Varela, Marta Lam, Hak-Keung Celiktutan, Oya Evans, Ben R. Coca-Castro, Alejandro Wu, Honghan Abdallah, Zahraa S. Chen, Chen Danchev, Valentin Tkachenko, Nataliya Lu, Lei Zhu, Tingting Slabaugh, Gregory G. Moore, Roger K. Cheung, William K. Charlton, Peter H. Lu, Haiping Centre for Machine Intelligence University of Sheffield Sheffield United Kingdom School of Computer Science University of Sheffield Sheffield United Kingdom The Alan Turing Institute London United Kingdom Department of Metabolism Digestion and Reproduction Imperial College London London United Kingdom Department of Applied AI Simula Research Laboratory Oslo Norway Information School University of Sheffield Sheffield United Kingdom NHS England Leeds United Kingdom Institute of Health Informatics University College London London United Kingdom Department of Engineering King’s College London London United Kingdom Department of Computing Science University of Aberdeen Aberdeen United Kingdom School of Informatics University of Edinburgh Edinburgh United Kingdom School of Engineering Mathematics and Technology University of Bristol Bristol United Kingdom Department of Informatics King’s College London London United Kingdom Department of Earth Sciences University of Cambridge Cambridge United Kingdom Department of Computer Science University of Manchester Manchester United Kingdom Department of Computer Science Queen Mary University of London London United Kingdom Digital Environment Research Institute Queen Mary University of London London United Kingdom Department of Computer Science University of Bath Bath United Kingdom Department of Classics King’s College London London United Kingdom School of Electrical Electronic and Mechanical Engineering University of Bristol Bristol United Kingdom School of Engineering University of the West of England Bristol United Kingdom Cancer Research UK Scotland Institute Glasgow United Kingdom School of Business and Management Queen Mary University of London London United Kingdom City St George’s University of London London United Kingdom British Antarctic Survey Cambridge United Kingdom School of Health and Wellbeing University of Glasgow Glasgow United Kingdom Chief Data & AI Office Lloyds Banking Group Lo

Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-making across disciplines such as healthcare, science, and engineering. However, most multimodal AI advances focus on models for vision and language data, while their deployability remains a key challenge. We advocate a deployment-centric workflow that incorporates deployment constraints early to reduce the likelihood of undeployable solutions, complementing data-centric and model-centric approaches. We also emphasise deeper integration across multiple levels of multimodality and multidisciplinary collaboration to significantly broaden the research scope beyond vision and language. To facilitate this approach, we identify common multimodal-AI-specific challenges shared across disciplines and examine three real-world use cases: pandemic response, self-driving car design, and climate change adaptation, drawing expertise from healthcare, social science, engineering, science, sustainability, and finance. By fostering multidisciplinary dialogue and open research practices, our community can accelerate deployment-centric development for broad societal impact. © 2025, CC BY.

关键词： Decision making

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P120 The relationship between digital technology and sleep-wake behaviour in children aged 5-8 years

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Sleep Advances 2024年第SUPPLEMENT_1期5卷 A70–A70页

作者： Pattinson, C Edmed, S Rossa, K Mann, D MacKenzie, J de Waal, L Smith, S Child Health Research Centre The University of Queensland South Brisbane Australia The Australian Research Council Centre of Excellence for Children and Families over the Life Course The University of Queensland Brisbane Australia The Australian Research Council Centre of Excellence for the Digital Child The University of Queensland Brisbane Australia School of School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia The Australian Research Council Centre of Excellence for the Digital Child Queensland University of Technology Brisbane Australia Institute for Social Science Research The University of Queensland Indooroopilly Australia

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