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Iranian Conference on electrical engineering (ICEE)

作者： Mohammad Amirkhani Ehsan Farmahini Farahani Alireza Eikani Mojtaba Mirsalim Javad Shokrollahi Moghani Department of Electrical Engineering Electrical Machines and Transformers Research Laboratory Amirkabir University of Technology Tehran Iran Electrical Power Research Group School of Engineering Newcastle University Newcastle upon Tyne U.K Advanced Motion Systems Research Lab School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Electrical Engineering Amirkabir University of Technology Tehran Iran

ISBN: (数字)9798350376340

ISBN: (纸本)9798350376357

This paper analyses three prominent biased-flux permanent magnet (BFPM) motors and compares them with each other. The structures of these BFPMs are different from each other, but they share the same operation principle. These structures are, namely, hybrid-excited multi-tooth slot-PM (HETSPM), multi-tooth variable flux reluctance (TVFR), and inter-modular PM (IMPM). The reason for this selection of structure is because of complementary features that each one possesses. For example, the HETSPM motor places in between the TVFR and IMPM motors in terms of PM consumption and demagnetization. However, the IMPM structure produces high amount torque at high efficiency. The demagnetization of the HETSPM and IMPM structures is also investigated and is shown that, in the similar situation, the HETSPM provides a safer operation environment for the PMs. Two-dimensional finite element method is used to extract the important profiles of the mentioned structures.

关键词： electrical engineering Magnetic flux Torque Motors Permanent magnets Finite element analysis Topology

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OVER-PARAMETERIZED MODEL OPTIMIZATION WITH POLYAK-LOJASIEWICZ CONDITION

OVER-PARAMETERIZED MODEL OPTIMIZATION WITH POLYAK-LOJASIEWIC...

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11th International Conference on Learning Representations, ICLR 2023

作者： Chen, Yixuan Shi, Yubin Dong, Mingzhi Yang, Xiaochen Li, Dongsheng Wang, Yujiang Dick, Robert P. Lv, Qin Zhao, Yingying Yang, Fan Gu, Ning Shang, Li China and Shanghai Key Laboratory of Data Science School of Computer Science Fudan University Shanghai China School of Mathematics Statistics The University of Glasgow Glasgow United Kingdom Microsoft Research Asia Shanghai China Department of Engineering Science University of Oxford Oxford United Kingdom Department of Electrical Engineering and Computer Science University of Michigan Michigan United States Department of Computer Science University of Colorado Boulder BoulderCO United States School of Microelectronics Fudan University Shanghai China

This work pursues the optimization of over-parameterized deep models for superior training efficiency and test performance. We first theoretically emphasize the importance of two properties of over-parameterized models, i.e., the convergence gap and the generalization gap. Subsequent analyses unveil that these two gaps can be upper-bounded by the ratio of the Lipschitz constant and the Polyak-Lojasiewicz (PL) constant, a crucial term abbreviated as the condition number. Such discoveries have led to a structured pruning method with a novel pruning criterion. That is, we devise a gating network that dynamically detects and masks out those poorly-behaved nodes of a deep model during the training session. To this end, this gating network is learned via minimizing the condition number of the target model, and this process can be implemented as an extra regularization loss term. Experimental studies demonstrate that the proposed method outperforms the baselines in terms of both training efficiency and test performance, exhibiting the potential of generalizing to a variety of deep network architectures and tasks. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Network architecture

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Optimal Bidding Strategy for a Wind Power Producer in the Energy and Spinning Reserve Markets

Optimal Bidding Strategy for a Wind Power Producer in the En...

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2021 North American Power Symposium, NAPS 2021

作者： Stratman, Anne Qiao, Wei Qu, Liyan University of Nebraska-Lincoln Power and Energy Systems Laboratory Department of Electrical and Computer Engineering LincolnNE68588-0511 United States

ISBN: (纸本)9781665420815

Wind power is one of the world's fastest-growing renewable energy resources. To achieve high levels of wind power penetration in the power supply, it will be necessary for wind power producers (WPPs) to contribute to system-wide reserves. This paper proposes a stochastic optimization model to determine the optimal offer strategy for a WPP that participates in the day-ahead and real-time energy and spinning reserve markets. The objective function maximizes the WPP's total expected profit while minimizing risk by allowing the WPP to split day-ahead offers between the energy and spinning reserve markets, which have lower penalties than the energy market for failing to deliver the cleared day-ahead offer. The model is solved using the simplex method, and hourly offer curves are generated for several levels of risk-aversion. Case study results show that the proposed offer strategy increases expected profit and significantly decreases risk compared to the case where the WPP only participates in the energy market. © 2021 IEEE.

关键词： Wind power

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Multi-Unit Floor Plan Recognition and Reconstruction Using Improved Semantic Segmentation of Raster-Wise Floor Plans

arXiv

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arXiv 2024年

作者： Kratochvila, Lukas de Jong, Gijs Arkesteijn, Monique Bilík, Šimon Zemčík, Tomáš Horak, Karel Rellermeyer, Jan S. Department of Control and Instrumentation Faculty of Electrical Engineering and Communication Brno University of Technology Brno Czech Republic Department of Software Technology Faculty of Electrical Engineering Mathematics and Computer Science TU Delft Delft Netherlands Department of Management in the Built Environment Faculty of Architecture and the Built Environment TU Delft Delft Netherlands Computer Vision and Pattern Recognition Laboratory Department of Computational Engineering Lappeenranta-Lahti University of Technology LUT Lappeenranta Finland Dependable and Scalable Software Systems Institute of Systems Engineering Faculty of Electrical Engineering and Computer Science Leibniz University Hannover Hannover Germany

Digital twins have a major potential to form a significant part of urban management in emergency planning, as they allow more efficient designing of the escape routes, better orientation in exceptional situations, and faster rescue intervention. Nevertheless, creating the twins still remains a largely manual effort, due to a lack of 3D-representations, which are available only in limited amounts for some new buildings. Thus, in this paper we aim to synthesize 3D information from commonly available 2D architectural floor plans. We propose two novel pixel-wise segmentation methods based on the MDA-Unet and MACU-Net architectures with improved skip connections, an attention mechanism, and a training objective together with a reconstruction part of the pipeline, which vectorizes the segmented plans to create a 3D model. The proposed methods are compared with two other state-of-the-art techniques and several benchmark datasets. On the commonly used CubiCasa benchmark dataset, our methods have achieved the mean F1 score of 0.86 over five examined classes, outperforming the other pixel-wise approaches tested. We have also made our code publicly available to support research in the field. © 2024, CC BY.

关键词： Semantic Segmentation

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Innate Cyber-Immunity and Acquired Cyber-Immunity across Multi-Area Power systems

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IEEE Transactions on Power systems 2025年

作者： Hou, Jiazuo Song, Yue Hou, Yunhe Peng, Jimmy Chih-Hsien National University of Singapore Department of Electrical and Computer Engineering Singapore Tongji University Department of Control Science and Engineering National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai Institute of Intelligent Science and Technology Shanghai201804 China The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong University of Hong Kong Shenzhen Institute of Research and Innovation Shenzhen518057 China

Organisms have evolved innate and acquired immune systems to defend against pathogens like coronaviruses. Similarly, power networks, threatened by cyber-attacks, desire cyber-immunity. Inspired by the immunology research, this study develops a cyber-immune strategy-characterizing innate cyber-immunity and establishing acquired cyber-immunity-for any selected portion of a power network (termed as power subnetwork) against stealthy false data injection (FDI) cyberattacks. Therein, without extrinsic protection and information asymmetry, this paper for the first time confirms the existence and provides closed-form conditions for power subnetworks that are innately immune to FDI cyber-attacks despite all measurements being compromised. Single-leader-multi-follower bi-level optimization models are then developed to strategically allocate measurement protection, leading to the acquired cyber-immunity, whose conditions for existence and the least cost are explicitly formulated. More importantly, a bi-directional cyber-immunity propagation mechanism is presented to provide the optimal spatial allocation of defense resources across adjacent subnetworks. It also explicitly determines the temporal allocation sequence, revealing its sequential and cumulative impacts on establishing cyber-immunity. This is achieved by designing recursive traversal algorithms, one of which is modelled as a post-order depth-first-search problem of a multi-fork tree. The proposed subnetwork-specific cyber-immune strategy is verified in a modified Australian National Electricity Market. © 1969-2012 IEEE.

关键词： Phishing

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Intelligent Control Based in Neural-Fuzzy of Adaptive Backstepping for The Double Stator IPMSM Powered by a Five-Level NPC Inverter

Intelligent Control Based in Neural-Fuzzy of Adaptive Backst...

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Electric And Power engineering (EPEi), IEEE International Conference And Exposition On

作者： Rabie Benaissa Smail Mansouri Omar Ouledali Department of Electrical Engineering Laboratory for Sustainable Development and Computer Science Faculty of Sciences and Technology University of Adrar Algeria Department of Hydrocarbons and Renewable Energies Laboratory for Energy Environment and Information Systems Faculty of Sciences and Technology University of Adrar Algeria

ISBN: (数字)9798350356199

ISBN: (纸本)9798350356205

This article supplies a proposed approach Neuro Fuzzy Controller (NFC)-Adaptive Backstepping Controller (ABC)-Space Vector Modulation (SVM) for a five-level NPC inverter-Double Stator Interior Permanent Magnet Synchronous Motor (DSIPMSM). This paper’s primary objective is to enhance DSIPMSM’s performance by the use of strong control using the proposed approach. Given its benefits—including high torque density, high efficiency, high power density, and minimal maintenance—DSIPMSM, have recently been the focus of much research. Using the input-output linearization approach and Lyapunov stability theory, asymptotically stable trajectory-following dynamics are demonstrated using nonlinear adaptive backstepping control. The use of fuzzy logic and intelligence-based controllers are increasingly being used to enhance traditional control’s performance and output. In addition, the fuzzy logic controller has a lot of flaws that are presently being fixed by the extremely effective NFC tool. The proposed method’s worth was demonstrated by the simulation results in terms of durability, effective tracking dynamics, precision, and good disturbance rejection with little ripple.

关键词： Fuzzy logic Adaptation models Backstepping Torque Simulation Modulation Stators Vectors Inverters Lyapunov methods

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Evaluating Large Language Models in Interaction with Open Government Data 24

Evaluating Large Language Models in Interaction with Open Go...

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Proceedings of the 28th Pan-Hellenic Conference on Progress in Computing and Informatics

作者： Ioannis Maslaris Areti Karamanou Evangelos Kalampokis Konstantinos Tarabanis Database & Information Retrieval Laboratory Department of Electrical & Computer Engineering Democritus University of Thrace Xanthi Greece Information Systems Laboratory Department of Business Administration University of Macedonia Thessaloniki Greece Information Technologies Institute Center for Research & Technology HELLAS (CERTH) Thessaloniki Greece and Information Systems Laboratory Department of Business Administration University of Macedonia Thessaloniki Greece

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A Dual-Inductor Quad-Path Hybrid Buck (2L4PHB) Converter With Reduced Inductor Current

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IEEE Journal of Solid-State Circuits 2025年

作者： Zeng, Wen-Liang Cai, Guigang Lu, Yan Sin, Sai-Weng Martins, Rui P. Lam, Chi-Seng State Key Laboratory of Analog and Mixed-Signal Vlsi University of Macau Macau999078 China Institute of Microelectronics University of Macau Macau999078 China Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States Guangzhou510530 China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau999078 China Department of Electronic Engineering Tsinghua University Beijing100084 China Instituto Superior Tecnico Universidade de Lisboa Lisbon1049-001 Portugal

In high-efficiency 12-to-1-1.8-V applications, the small duty ratio (D ≈ 0.1) and high voltage stress on power switches of the conventional buck converter bring significant efficiency penalty. This article proposes a dual-inductor quad-path hybrid buck (2L4PHB) converter that addresses these issues, achieving both high power conversion efficiency and power density. Compared to the widely used double step-down (DSD) converter, the proposed 2L4PHB converter reduces the average inductor current by 30% and the inductor current ripple by 18% at a voltage conversion ratio (VCR) of 0.15. In addition to continuous conduction mode (CCM), this design incorporates a discontinuous conduction mode (DCM) calibration loop to improve efficiency at light loads. The proposed 2L4PHB converter, fabricated in a 180-nm BCD process, achieves a maximum current density of 0.18 A/mm2 and 256 A/cm3 and a peak efficiency of 93.7% and maintains efficiencies above 85% across load currents ranging from 0.6 to 4 A, all while using a compact inductor with dimensions of 2.5 × 2.0 × 1.0 mm3 and a DCR of 48 mΩ. © 2025 IEEE.

关键词： Buck converter

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Accelerated Saddle Flow Dynamics for Bilinearly Coupled Minimax Problems

Accelerated Saddle Flow Dynamics for Bilinearly Coupled Mini...

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IEEE Conference on Decision and Control

作者： Yingzhu Liu Enrique Mallada Zhongkui Li Pengcheng You College of Engineering Peking University Beijing China State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Minimax problems have attracted much attention due to various applications in constrained optimization problems and zero-sum games. Identifying saddle points within these problems is crucial, and saddle flow dynamics offer a straightforward yet useful approach. This study focuses on a class of bilinearly coupled minimax problems with strongly convex-linear objective functions. We design an accelerated algorithm based on saddle flow dynamics, achieving a convergence rate beyond the stereotype limit (the strong convexity constant). The algorithm is derived from a sequential two-step transformation of a given objective function. First, a change of variables is applied to render the objective function better-conditioned, introducing strong concavity (from linearity) while preserving strong convexity. Second, proximal regularization, when staggered with the first step, further enhances the strong convexity of the objective function by shifting some of the obtained strong concavity. After these transformations, saddle flow dynamics based on the new objective function can be tuned for accelerated exponential convergence. Besides, such an approach can be extended to weakly convex-weakly concave functions and still guarantees exponential convergence to one stationary point. The theory is verified by a numerical test on an affine equality-constrained convex optimization problem.

关键词： Couplings Heuristic algorithms Linearity Games Linear programming Convex functions Game theory Optimization Convergence

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Meet the Co-Editor

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Micro and Nanosystems 2022年第3期14卷 187-187页

作者： Deen, Jamal Nano-Systems Laboratory Department Electrical Computer Engineering & School of Biomedical Engineering McMaster University HamiltonON Canada

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