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arXiv 2024年

作者： Broens, Yorick Butler, Hans Tóth, Roland The Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands ASML Veldhoven Netherlands The Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Hungary

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator *** Codes 37M15 © 2024, CC BY.

关键词： Continuous time systems

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Additively Manufactured Strain Sensing for Nuclear Reactor Applications 13

Additively Manufactured Strain Sensing for Nuclear Reactor A...

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13th Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies, NPIC and HMIT 2023

作者： Phero, Timothy L. Novich, Kaelee A. Fujimoto, Kiyo T. Khanolkar, Amey R. Johnson, Benjamin C. McMurtrey, Michael D. Estrada, David Jaques, Brian J. Micron School of Materials Science and Engineering Boise State University BoiseID United States Department of Electrical and Computer Engineering Boise State University BoiseID United States Center for Advanced Energy Studies Idaho FallsID United States Idaho National Laboratory Idaho FallsID United States

ISBN: (纸本)9780894487910

Real-time monitoring of materials in harsh environments is a crucial technique towards reducing innovation time in nuclear systems. The successful measurement of real time, in-situ strain measurements during nuclear reactor operation requires innovative sensing solutions, including novel sensing strategies as well as advanced sensor design, manufacturing, and materials selection. In this paper, we will discuss two primary strategies for in-situ strain measurement strategies: additively manufactured (AM) capacitive strain gauges (CSGs) and digital image correlation (DIC). Current commercial strain gauges have limited applications in reactors due to the harsh operating conditions and non-trivial attachment strategies (i.e., welding, epoxy-adhesive) that can affect both the sensing performance and the underlying substrate under testing. AM CSGs are a viable solution as they have a low profile, low hysteresis, and wireless sensing integration capabilities that will enhance nuclear sensing technologies. In this work, the mechanical and thermal performance of the AM CSGs were tested up to 300 °C using ASTM standardized testing procedures to simulate the temperatures found in existing light water reactors. The AM CSGs had a similar performance across multiple samples which correlates to analytical models. This work leads towards the development of CSGs designed for higher temperatures and additional environmental factors found in Generation-IV reactors. Non-contact sensors, such as DIC, offer a less destructive way to measure deformation of materials when compared to alternative methods of in-situ strain determination, such as weldable strain gauges. However, DIC requires high contrast surfaces, which often relies on the implementation of artificial patterns. Using traditional splatter techniques to fabricate these patterns have limitations, including poor surface adhesion and reproducibility. In this work, AM fabrication techniques were implemented to avoid such limitatio

关键词： Image correlation

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Pointsurface: Discriminative Point Cloud Surface Feature Extraction for 3d Face Recognition

SSRN

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SSRN 2024年

作者： Yang, Junpeng Li, Qiufu Shen, Linlin Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Guangdong Shenzhen518060 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Guangdong Shenzhen518060 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen University Guangdong Shenzhen518172 China

3D face recognition performs better than 2D face recognition, in terms of robustness against lighting and digital attacks. Compared to 2D data, the rich geometric information in 3D data could be very useful to improve the performance of 3D face recognition. This paper introduces PointSurFace, a surface feature extraction integrated model tailored for point cloud based 3D face recognition. PointSurFace adopts a specially designed surface feature extraction module, which explores information about the position and normals of the 3D face surface to explicitly extract local discriminative features from 3D point cloud faces. Subsequently, it alternates between set abstraction (SA) layers and Inverted Residual MLP (InvResMLP) modules to effectively extract features from the point cloud data. To better handle the spatial relationships in the point cloud data, PointSurFace integrates coordinate and feature data within each SA layer and InvResMLP module. It also applies channel fusion operations to align these different types of data, thereby more effectively extracts point cloud features. Experimental results in 3D facial recognition and verification across multiple datasets demonstrate that PointSurFace achieves the best 3D face recognition performance to date. For example, on Lock3DFace, it achieves the state-of-the-art recognition and verification accuracy of 90.03% and 80.01%, respectively, surpassing previous methods by 2.02% and 3.19%. Results on cross-quality datasets also affirm PointSurFace’s strong generalization capabilities. Ablation experiments validate the effectiveness of each module within PointSurFace, which suggests that the proposed surface feature extraction module significantly enhances the point cloud based 3D facial recognition performance. © 2024, The Authors. All rights reserved.

关键词： Feature extraction

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Dynamic Graph Neural Networks for Joint Terahertz based Sensing and Communication Optimization in Vehicular Networks

Dynamic Graph Neural Networks for Joint Terahertz based Sens...

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IEEE Conference on Wireless Communications and Networking

作者： Xuefei Li Mingzhe Chen Ye Hu Zhilong Zhang Danpu Liu Shiwen Mao Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijina China Department-of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Coral Gables FL USA Department of Industrial and System Engineering University of Miami Coral Gables FL USA Department of Electrical and Computer Engineering Auburn University Auburn AL USA

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

In this paper, the problem of vehicle service mode selection (sensing, communication, or both) and vehicle connections within terahertz (THz) enabled joint sensing and communications over vehicular networks is studied. The considered network consists of several service provider vehicles (SPVs) that can provide: 1) only sensing service, 2) only communication service, and 3) both services, sensing service request vehicles, and communication service request vehicles. Based on the vehicle network topology and their service accessibility, SPVs strategically select service request vehicles to provide sensing, communication, or both services. This problem is formulated as an optimization problem, aiming to maximize the number of successfully served vehicles by jointly determining the service mode of each SPV and its associated vehicles. To solve this problem, we propose a dynamic graph neural network (GNN) model that selects appropriate graph information aggregation functions according to the vehicle network topology, thus extracting more vehicle network information compared to traditional static GNNs that use fixed aggregation functions for different vehicle network topologies. Using the extracted vehicle network information, the service mode of each SPV and its served service request vehicles will be determined. Simulation results show that the proposed dynamic GNN based scheme can improve the number of successfully served vehicles by up to 17% compared to a GNN based algorithm with a fixed neural network model.

关键词： Network topology Simulation Heuristic algorithms Graph neural networks Sensors Data mining Vehicle dynamics

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P-HIL Model Development for MW Charging Sites Incorporating Real-World XFC Load Profiles

P-HIL Model Development for MW Charging Sites Incorporating ...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Sadam Ratrout Daniel Dobrzynski Bryan Nystrom Sam Thurston Mahesh Krishnamurthy Department of Electrical and Computer Engineering Illinois Institute of Technology Chicago IL USA Advanced Mobility and Grid Integration Department Argonne National Laboratory Lemont IL USA

ISBN: (数字)9798350317664

ISBN: (纸本)9798350317671

This paper develops a P-HIL model to analyze the real-world impact of XFC charging profiles on the grid frequency. Using charging profiles captured for different EVs and E-trucks at different start SoC and temperature conditions, a database of 93 profiles was used to develop a MW-level charging site scenario. The scenario envisions a charging site with EVSE usage that is mixed for fleet charging at a small business with public charging availability when fleet charging is undesired. A statistical study of 1446 DCFC and XFC charging sessions was conducted to identify start and end SoCs and develop the expected load profiles. Two real-world XFCs and BESS have been connected to a real-time digitally simulated modified IEEE 37-bus distribution grid and run on an Opal-RT real-time digital simulator. Several communication protocols, including UDP, Modbus, OCPP, and TCP have been employed in the associated MQTT IoT environment. This model can be used to design the optimal control strategy that could determine the amount of injected or absorbed active power from the co-located BESS to mitigate the effect of running a large number of XFCs clusters on the grid frequency and rate of change of frequency.

关键词： Analytical models Protocols Databases Transportation Optimal control Electrification Real-time systems

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Biphoton spectral quantum interference for information processing and delay metrology 3

Biphoton spectral quantum interference for information proce...

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Quantum Computing, Communication, and Simulation III 2023

作者： Seshadri, Suparna Lu, Hsuan-Hao Lukens, Joseph M. Weiner, Andrew M. School of Electrical and Computer Engineering Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Quantum Information Science Section Oak Ridge National Laboratory Oak RidgeTN37831 United States Research Technology Office Arizona State University TempeAZ85287 United States

ISBN: (纸本)9781510659971

Broadband time-energy entangled photons feature strong temporal correlations with potential for precision delay metrology, but previous work has leveraged only time-of-flight information ultimately limited by the detection jitter and resolution of the time-tagging electronics. Firstly, our work pushes the entanglement-based nonlocal delay metrology from the conventional time-of-flight measurement to a new direction—two-photon interferometry with subpicosecond sensitivity independent of detection resolution. Next, we show the selective sensitivity of frequency-bin encoded Bell states to the sum and difference of biphoton-delays by using a novel reconfigurable setup capable of switching between the Bell states by successively employing single and dual spectral-line pumps. © 2023 SPIE.

关键词： Photons

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FEDERATED LEARNING WITH DYNAMIC CLIENT ARRIVAL AND DEPARTURE: CONVERGENCE AND RAPID ADAPTATION VIA INITIAL MODEL CONSTRUCTION

arXiv

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arXiv 2024年

作者： Chang, Zhan-Lun Han, Dong-Jun Parasnis, Rohit Hosseinalipour, Seyyedali Brinton, Christopher G. Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Department of Computer Science and Engineering Yonsei University Seoul Korea Republic of The Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering University at Buffalo-SUNY BuffaloNY14260 United States

While most existing federated learning (FL) approaches assume a fixed set of clients in the system, in practice, clients can dynamically leave or join the system depending on their needs or interest in the specific task. This dynamic FL setting introduces several key challenges: (1) the objective function dynamically changes depending on the current set of clients, unlike traditional FL approaches that maintain a static optimization goal;(2) the current global model may not serve as the best initial point for the next FL rounds and could potentially lead to slow adaptation, given the possibility of clients leaving or joining the system. In this paper, we consider a dynamic optimization objective in FL that seeks the optimal model tailored to the currently active set of clients. Building on our probabilistic framework that provides direct insights into how the arrival and departure of different types of clients influence the shifts in optimal points, we establish an upper bound on the optimality gap, accounting for factors such as stochastic gradient noise, local training iterations, non-IIDness of data distribution, and deviations between optimal points caused by dynamic client pattern. We also propose an adaptive initial model construction strategy that employs weighted averaging guided by gradient similarity, prioritizing models trained on clients whose data characteristics align closely with the current one, thereby enhancing adaptability to the current clients. The proposed approach is validated on various datasets and FL algorithms, demonstrating robust performance across diverse client arrival and departure patterns, underscoring its effectiveness in dynamic FL environments. © 2024, CC BY.

关键词： Federated learning

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Graph-Based Visual-Kinematic Fusion and Monte Carlo Initialization for Fast-Deployable Cable-Driven Robots

Graph-Based Visual-Kinematic Fusion and Monte Carlo Initiali...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： R. Khorrambakht H. Damirchi M.R. Dindarloo A. Saki S.A. Khalilpour Hamid D. Taghirad Stephan Weiss Electrical & Computer Engineering Department Control/Robotics Research Laboratory Tandon School of Engineering New York University Brooklyn NY School of Computer Science University of Adelaide Australia Faculty of Electrical Engineering University of Technology Tehran Iran Department of Smart Systems Technologies University of Klagenfurt Austria

Ease of calibration and high-accuracy task-space state-estimation purely based on onboard sensors is a key requirement for enabling easily deployable cable robots in real-world applications. In this work, we incorporate the onboard camera and kinematic sensors to drive a statistical fusion framework that presents a unified localization and calibration system which requires no initial values for the kinematic parameters. This is achieved by formulating a Monte-Carlo algorithm that initializes a factor-graph representation of the calibration and localization problem. With this, we are able to jointly identify both the kinematic parameters and the visual odometry scale alongside their corresponding uncertainties. We demonstrate the practical applicability of the framework using our state-estimation dataset recorded with the ARAS-CAM suspended cable driven parallel robot, and published as part of this manuscript.

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Securing Overlay Cognitive Radio Networks Over Cascaded Channels with Energy Harvesting

Securing Overlay Cognitive Radio Networks Over Cascaded Chan...

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IEEE Globecom Workshops

作者： Deemah H. Tashman Soumaya Cherkaoui Walaa Hamouda Sidi Mohammed Senouci Department of Computer and Software Engineering Polytechnique Montreal Montreal Canada Department of Electrical and Computer Engineering Concordia-University Montreal Canada DRIVE Laboratory EA1859 Univ. Bourgogne Franche Comté Nevers France

This paper investigates the physical-layer security (PLS) for an overlay cognitive radio network (CRN). Due to the unreliability of direct communication between the primary users (PUs), secondary users (SUs) are enlisted to facilitate communication between two PUs. As several SUs are available, a particular one is chosen to transmit the PUs' messages in addition to its own. This SU uses the time switching protocol to harvest power from the PU's signal. Additionally, an eavesdropper is available to capture the messages conveyed by the PUs. Given this, the SU receiver collects energy from the relayed messages through the power splitting protocol and utilizes this energy to transmit jamming signals in order to degrade the wiretap channel and improve the privacy of the PUs' communication. The signals' transmission is modeled more realistically under the assumption of cascaded Rayleigh channels. The performance of PLS is evaluated using the probability of a non-zero secrecy capacity and the intercept probability. Moreover, the SUs' Ergodic rate is studied to analyze the impact of this assistance on their transmission reliability.

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Integrating Sustainability and Industry 4.0: A Framework for Sustainable Logistics 4.0

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Circular Economy and Sustainability 2025年第3期5卷 2157-2195页

作者： Di Nardo, Mario Gallab, Maryam Murino, Teresa Wu, Jing Pandey, Shatrudhan Facoltàdi Ingegneria Università Telematica Pegaso Rome 00186 Italy MIS-LISTD Laboratory Computer Science Department Mines-Rabat School (ENSMR) Rabat 10000 Morocco Department of Chemical Materials and Industrial Production Engineering University of Naples “Federico II” Naples Italy Department of Electrical and Photonics Engineering Technical University of Denmark Kgs. Lyngby 2800 Denmark Marwadi University Research Center Faculty of Management Studies Marwadi University Gujarat Rajkot 360003 India

As society becomes more aware of environmental and social issues, supply chain stakeholders increasingly consider these factors alongside efficiency, cost, and time. The logistics industry must adapt by integrating Industry 4.0 technologies and sustainability practices. Sustainable Logistics 4.0, though nascent, is gaining traction for enhancing sustainability through digital interventions. This study conducted a comprehensive literature review and bibliometric network analysis using data extracted from the Scopus and Google Scholar databases, covering the period from 2013 to 2023, focusing on the integration of sustainability, Industry 4.0, and logistics. Noting a gap in conceptual frameworks, the paper performs a SWOT analysis to identify key factors and proposes a framework for digitalizing sustainable logistics and addressing emerging challenges. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Circular Economy Industry 4.0 Logistics Sustainability TBL

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