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IEEE National Conference on Aerospace and Electronics (NAECON)

作者： Isaac E. Weintraub Alexander Von Moll Meir N. Pachter Control Science Center Air Force Research Laboratory Wright-Patterson AFB OH Electrical and Computer Engineering Air Force Institute of Technology Wright-Patterson AFB OH

A turn-constrained evader strives to escape a circular region in minimum time.

ISBN: (数字)9798350367621

ISBN: (纸本)9798350367638

A turn-constrained evader strives to escape a circular region in minimum time.

关键词： Geometry Aerospace electronics Automobiles

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The Entrapment Problem in Random Walk Decentralized Learning

The Entrapment Problem in Random Walk Decentralized Learning

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IEEE International Symposium on Information Theory

作者： Zonghong Liu Salim El Rouayheb Matthew Dwyer Department of Electrical and Computer Engineering Rutgers University New Brunswick NJ USA Network Cyber and Computational Sciences Division DEVCOM Army Research Laboratory Adelphi MD USA

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

This paper explores decentralized learning in a graph-based setting, where data is distributed across nodes. We investigate a decentralized SGD algorithm that utilizes a random walk to update a global model based on local data. Our focus is on designing the transition probability matrix to speed up convergence. While importance sampling can enhance centralized learning, its decentralized counterpart, using the Metropolis-Hastings (MH) algorithm, can lead to the entrapment problem, where the random walk becomes stuck at certain nodes, slowing convergence. To address this, we propose the Metropolis-Hastings with Levy Jumps (MHLJ) algorithm, which incorporates random perturbations (jumps) to overcome entrapment. We theoretically establish the convergence rate and error gap of MHLJ and validate our findings through numerical experiments.

关键词： Monte Carlo methods Perturbation methods Distributed databases Data models Convergence Information theory

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A computational and experimental mechanical study of nanocomposites for 3D printed scaffolds with a new geometry

A computational and experimental mechanical study of nanocom...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： S.V. Kallivokas L. Kontaxis I. Kakkos D. Deligianni V. Kostopoulos G. K. Matsopoulos Biomedical Engineering Laboratory School of Electrical and Computer Engineering National Technical University of Athens Greece Zografou Greece Mechanical Engineering Department University of Patras Rio Achaia Greece

We present a combined study of the mechanical properties of 3D printed scaffolds made by nanocomposite materials based on polycaprolactone (PCL). The geometry and dimensions of the three different systems is the same. Τhe porosity is 50% for all systems. Distributions of von-Mises strains and stresses, and total deformations were obtained through Finite Element Analysis (FEA) for a maximum amount of force applied, in a compressive numerical experiment. Also compressive experiments were performed for both raw and 3D nanoconposite scaffolds.

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Bilevel Nodal Behind-the-meter Solar Disaggregation Under Unexpected Extreme Weather Conditions

Bilevel Nodal Behind-the-meter Solar Disaggregation Under Un...

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IEEE General Meeting Power& Energy Society

作者： Daniel Moscovitz Zhenyu Zhao Liang Du Xiaoyuan Fan EMS Support Department PJM Interconnection Audubon USA Dept. of Electrical & Computer Engineering Temple University Philadelphia USA Pacific Northwest National Laboratory Richland USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

As the power grid undergoes significant paradigm shift due to the increasing penetration of renewable generation, the ever-growing installation of behind-the-meter (BTM) solar generation in the power grid also has a significant impact on nodal loads, posing challenges on transmission operators. Furthermore, increasing frequent and severe extreme weather events intertwine with ubiquitous BTM solar generations and have amplified the challenges of accurately model nodal load profiles, especially under the lack of ground-truth information for verification. To tackle these challenges, this paper introduces a bilevel model that utilizes year-long data (e.g., proxy solar, zonal load, and individual node load profiles) to disaggregate metered profiles into actual demand and BTM solar generation at each transmission node. The proxy solar not only scales the BTM solar generation of individual nodes but also create a compensation term for enhancing performance on days with unexpected extreme weather events. The proposed algorithm is validated with real-world PJM Interconnection data during unexpected events like the recent Winter Storm Elliott. For quantitative evaluations, a novel Score error is introduced, which is based on mean percentages and load scales and offers a universal assessment method suitable for all nodes and different data formats (e.g., normalized or raw values).

关键词： Renewable energy sources Storms Power grids Data models Solar power generation Load modeling

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Modeling and Optimization of a Through-Metal Acoustic Wireless Power Transfer System

Modeling and Optimization of a Through-Metal Acoustic Wirele...

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IEEE Workshop on computers in Power Electronics

作者： Kody Froehle Daniel Costinett Sarah S. Bedair Victor Farm-Guoo Tseng Department of Electrical Engineering and Computer Science The University of Tennessee Knoxville TN USA U.S. Army Combat Capabilities Development Command Army Research Laboratory USA

ISBN: (数字)9798350307238

ISBN: (纸本)9798350307245

This paper presents the design of a through-metal acoustic wireless power transfer (AWPT) system using piezoelectric transducers (PT) as transmitter (TX) and receiver (RX). An equivalent circuit model using measured impedance parameters is used to model the complete PT-to-PT electromechanical conversion. The system is designed by sweeping frequency, load resistance, and compensation design to maximize transferred power. Boundary constraints are presented based on temperature and voltage limits the PTs can withstand. An optimal design staying within the operating bounds is then chosen and tested in hardware. The designed system is fabricated and verified experimentally for varying voltage levels. The prototype system has been tested up to 160 V dc input and 41 W output.

关键词： Temperature measurement Voltage measurement Transmitters Prototypes Wireless power transfer Thermal management Acoustics

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Sliding-Mode Based Model Predictive Control for Enhancing Robustness and Output Performance in Dynamic Inductive Power Transfer Systems

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Chan, Pak-Ian Ieong, Chi-Fong Iam, Io-Wa Lam, Chi-Seng University of Macau State Key Laboratory of Analog and Mixed-Signal VLSI 999078 China University of Macau Institute of Microelectronics 999078 China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering 999078 China

In dynamic inductive power transfer (DIPT) systems for automated guided vehicles (AGVs), the movement of the AGV can significantly impact the coupling coefficient, degrading the output performance. Conventional control methods, while capable of addressing this challenge, often exhibit weak robustness due to their sensitivity to circuit parameter variations and require trial-and-error process for tuning coefficients, thus increasing design complexity and difficulty. This paper proposes a sliding-mode based model predictive control (SM-MPC) approach tailored for DIPT systems to enhance robustness and output performance. The SM-MPC employs a predictive model to force the control object to converge to a sliding surface, leveraging fast dynamic response characteristics to mitigate AGV movement-induced disturbances. A pole-placement method is introduced to directly acquire the optimal sliding coefficient, eliminating iterative tuning requirements and simplifying the design process. Herein, the DIPT system model is presented, followed by the SM-MPC design methodology, stability analysis, and sliding coefficient design. Finally, simulations and experimental results validate the proposed SM-MPC’s effectiveness in stabilizing the output performance of DIPT systems, demonstrating improved robustness against parameter variations and disturbances caused by AGV movement compared to existing control methods. © 2013 IEEE.

关键词： Predictive control systems

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Transmit Power Minimization for IRS-Assisted NOMA-UAV Networks

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China Communications 2024年第5期21卷 137-152页

作者： Zhao Chen Pang Xiaowei Tang Jie Liu Mingqian Zhao Nan Zhang Xiuyin Wang Xianbin School of Information and Communication Engineering Dalian University of TechnologyDalian 116024China School of Electronic and Information Engineering South China University of TechnologyGuangzhou 510641China State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an 710071China Department of Electrical and Computer Engineering Western UniversityLondonON N6A 5B9Canada

The flexibility of unmanned aerial vehicles(UAVs)allows them to be quickly deployed to support ground *** reflecting surface(IRS)can reflect the incident signal and form passive beamforming to enhance the signal in the specific *** by the promising benefits of both technologies,we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with *** to their distance to the UAV,the users are divided into the close users and remote *** UAV hovers above the close users due to their higher rate requirement,while the IRS is deployed near the remote users to enhance their received *** aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding ***,the problem is ***,we decompose it into two sub-problems,including the transmit beamforming optimization and phase shift optimization,which are transformed into second-order cone programming and semidefinite programming,*** propose an iterative algorithm to solve the two sub-problems *** results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.

关键词： intelligent reflecting surface nonorthogonal multiple access phase shift optimization transmit beamforming optimization unmanned aerial vehicle

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Distributed Tomographic Reconstruction with Quantization

arXiv

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arXiv 2024年

作者： Miao, Runxuan Aslan, Selin Koyuncu, Erdem Gürsoy, Doǧa Department of Electrical and Computer Engineering University of Illinois Chicago United States Department of Mathematics Koc University Turkey Advanced Photon Source Argonne National Laboratory United States

Conventional tomographic reconstruction typically depends on centralized servers for both data storage and computation, leading to concerns about memory limitations and data privacy. Distributed reconstruction algorithms mitigate these issues by partitioning data across multiple nodes, reducing server load and enhancing privacy. However, these algorithms often encounter challenges related to memory constraints and communication overhead between nodes. In this paper, we introduce a decentralized Alternating Directions Method of Multipliers (ADMM) with configurable quantization. By distributing local objectives across nodes, our approach is highly scalable and can efficiently reconstruct images while adapting to available resources. To overcome communication bottlenecks, we propose two quantization techniques based on K-means clustering and JPEG compression. Numerical experiments with benchmark images illustrate the tradeoffs between communication efficiency, memory use, and reconstruction *** Codes 68W15, 65R32 © 2024, CC BY.

关键词： Differential privacy

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PCART: Automated Repair of Python API Parameter Compatibility Issues

arXiv

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arXiv 2024年

作者： Zhang, Shuai Xiao, Guanping Wang, Jun Lei, Huashan He, Gangqiang Liu, Yepang Zheng, Zheng The College of Computer Science and Technology The Key Laboratory for Safety-critical Software Development and Verification Nanjing University of Aeronautics and Astronautics Nanjing China The Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China The School of Automation Science and Electrical Engineering Beihang University Beijing China

In modern software development, Python third-party libraries play a critical role, especially in fields like deep learning and scientific computing. However, API parameters in these libraries often change during evolution, leading to compatibility issues for client applications reliant on specific versions. Python’s flexible parameter-passing mechanism further complicates this, as different passing methods can result in different API compatibility. Currently, no tool can automatically detect and repair Python API parameter compatibility issues. To fill this gap, we introduce PCART, the first solution to fully automate the process of API extraction, code instrumentation, API mapping establishment, compatibility assessment, repair, and validation. PCART handles various types of Python API parameter compatibility issues, including parameter addition, removal, renaming, reordering, and the conversion of positional to keyword parameters. To evaluate PCART, we construct PCBENCH, a large-scale benchmark comprising 47,478 test cases mutated from 844 parameter-changed APIs across 33 popular Python libraries. Evaluation results demonstrate that PCART is both effective and efficient, significantly outperforming existing tools (MLCatchUp and Relancer) and the large language model ChatGPT (GPT-4o), achieving an F1-score of 96.49% in detecting API parameter compatibility issues and a repair precision of 92.26%. Further evaluation on 30 real-world Python projects from GitHub confirms PCART’s practicality. We believe PCART can significantly reduce the time programmers spend maintaining Python API updates and advance the automation of Python API compatibility issue repair. Copyright © 2024, The Authors. All rights reserved.

关键词： Python

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Enhanced Detection of Demagnetization in Direct-Drive Wind Turbine Generators Using eMIST and Machine Learning

Enhanced Detection of Demagnetization in Direct-Drive Wind T...

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IEEE Workshop on electrical Machines Design, Control and Diagnosis (WEMDCD)

作者： Qiuyi Chen Panagiotis Tsilifis Jaime Renedo Anglada Department of Mechanical Engineering University of Maryland College Park MD USA Robotics AI & Computer Vision Group GE Vernova Advanced Research Niskayuna NY USA Electrical Systems GE Vernova Advanced Research Niskayuna NY USA

ISBN: (数字)9798331520748

ISBN: (纸本)9798331520755

The rapid growth of offshore wind energy needs robust condition monitoring to ensure the reliability and efficiency of direct-drive permanent magnet synchronous generators (PMSGs). Demagnetization, a critical fault in these generators, can severely impact performance and increase operational costs, especially in harsh marine environments. Traditional diagnostic techniques often struggle to detect subtle magnetic property changes under varying load conditions. This paper presents an innovative framework for demagnetization detection in PMSGs, leveraging the electrical Multi-phase Imbalance Separation Technique (eMIST) combined with machine learning models. Using a dataset from offshore wind turbines, including simulated faulty conditions, the proposed methodology enhances anomaly detection by isolating imbalance signatures and correlating them with key operational parameters. Gaussian Process Regression (GPR) is employed to predict anomalies, offering high accuracy and confidence in fault classification. Results demonstrate the approach's ability to identify early-stage demagnetization, enabling predictive maintenance, reducing downtime, and improving the economic viability of offshore wind farms.

关键词： Costs Accuracy Wind energy Machine learning Gaussian processes Wind farms Generators Wind turbines Demagnetization Anomaly detection

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