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4th International Conference on Energy, Power and electrical engineering, EPEE 2024

作者： Kan, Jinpeng Meng, Yongqing Li, Changyi Chen, Wenjie Li, Fengjiao Shi, Yixin Xi'an Jiaotong University School of Electrical Engineering Xi'an China Avic Xi'an Flight Automatic Control Research Institute Department of Computer and Electronic Systems Engineering Xi'an China

ISBN: (纸本)9798331518066

Power electronic switching devices and pulse width modulation (PWM) not only improves the performance of motor drive systems, but also brings about common-mode voltage (CMV) issues, that challenging the normal operation of the system. This article proposes a zero common-mode voltage modulation strategy based on unified voltage modulation for a 60° Y-connected six-phase permanent magnet synchronous motor system driven by a dual three-phase inverter. The theoretical basis and zero common-mode implementation scheme of unified modulation are analyzed, and the effectiveness of the proposed zero common-mode voltage modulation strategy is finally verified through simulation. © 2024 IEEE.

关键词： Pulse width modulation

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"Hi, My Name is Robin" – Remotely Co-designing an Embodied Conversational Agent for Empathy with Older Adults 9th

"Hi, My Name is Robin" – Remotely Co-designing an Embodied ...

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9th International Conference on Human Aspects of IT for the Aged Population, ITAP 2023, held as part of the 25th International Conference on Human-computer Interaction, HCII 2023

作者： Tunc, Sefora Nijboer, Femke Tinga, Angelica M. Tabak, Monique Biomedical Signals and Systems Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands Roessingh Research and Development Enschede Netherlands

ISBN: (纸本)9783031348655

Embodied conversational agents (ECAs) have the potential to facilitate empathic relationships between older adults and eHealth coaches, but little research has been conducted on how to effectively include appearance and personality in the design of ECAs such that older adults can empathize with the agent. In this study, we aimed first to develop design requirements for ECAs that induce empathy in older adults. Second, we developed and reflected upon a remote (online), iterative co-design methodology which can be used as an alternative when traditional physical methods cannot take place (e.g. during COVID-19). Over the course of three months, five older adults (mean age 68 years) 1) received a paper booklet, 2) were invited to an Q&A session, 3) after which they were asked develop their own ECAs at home using the booklet, 4) and came back to discuss their designs online in a group setting to determine design requirements, 5) which were used to develop an interactive ECA, 6) that was individually evaluated in an online meeting. The final ECA, called Robin, was positively perceived in terms of appearance, but the participants expected the conversation with Robin to be more flexible and deeper. Overall, the current study demonstrated the feasibility of remote co-design activities for this population and presents recommendations for researchers and practitioners interested in or in need for a remote approach. Moreover, the current findings are translated in lessons learnt to inform design and development of future ECAs for older adults. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Design

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Robust Stochastic Shortest-Path Planning via Risk-Sensitive Incremental Sampling 63

Robust Stochastic Shortest-Path Planning via Risk-Sensitive ...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Enwerem, Clinton Noorani, Erfaun Baras, John S. Sadler, Brian M. Institute for Systems Research University of Maryland Department of Electrical & Computer Engineering College ParkMD United States University of Texas at Austin TX United States

ISBN: (纸本)9798350316339

With the pervasiveness of Stochastic Shortest-Path (SSP) problems in high-risk industries, such as last-mile autonomous delivery and supply chain management, robust planning algorithms are crucial for ensuring successful task completion while mitigating hazardous outcomes. Mainstream chance-constrained incremental sampling techniques for solving SSP problems tend to be overly conservative and typically do not consider the likelihood of undesirable tail events. We propose an alternative risk-aware approach inspired by the asymptoticallyoptimal Rapidy-Exploring Random Trees (RRT*) planning algorithm, which selects nodes along path segments with minimal Conditional Value-at-Risk (CVaR). Our motivation rests on the step-wise coherence of the CVaR risk measure and the optimal substructure of the SSP problem. Thus, optimizing with respect to the CVaR at each sampling iteration necessarily leads to an optimal path in the limit of the sample size. We validate our approach via numerical path planning experiments in a two-dimensional grid world with obstacles and stochastic pathsegment lengths. Our simulation results show that incorporating risk into the tree growth process yields paths with lengths that are significantly less sensitive to variations in the noise parameter, or equivalently, paths that are more robust to environmental uncertainty. Algorithmic analyses reveal similar query time and memory space complexity to the baseline RRT∗ procedure, with only a marginal increase in processing time. This increase is offset by significantly lower noise sensitivity and reduced planner failure rates. © 2024 IEEE.

关键词： Stochastic systems

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On the Importance of Trust in Next-Generation Networked Cyber-Physical systems

On the Importance of Trust in Next-Generation Networked Cybe...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Nariman Torkzaban Anousheh Gholami John S. Baras Department of Electrical & Computer Engineering Institute for Systems Research

ISBN: (数字)9798350370997

ISBN: (纸本)9798350371000

With 5G and beyond promises to realize massive machine-type communications, a wide range of applications have driven interest in complex heterogeneous networked systems, including multi-agent optimization, large-scale distributed learning, 5G service provisioning, etc. This trend highlights the essence of seamless control, management, and security mechanisms to be in place for the next-generation networked cyber-physical systems (CPS). In this paper, we interpret trust as a relation among networked collaborating entities that can set forth a measure for evaluating the status of network components and secure the execution of the collaborative protocol. In this paper, we will first elaborate on the importance of trust as a metric and then present a mathematical framework for trust computation and aggregation within a network. We consider two use-case examples where trust can be incorporated into the next-generation networked CPS and improve the security of decision-making, i.e. i) federated learning (FL), and ii) network resource provisioning. Finally, we explain the challenges associated with aggregating the trust evidence and briefly explain our ideas to tackle them.

关键词： Measurement Protocols 5G mobile communication Federated learning Distance learning Cyber-physical systems Market research

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Enhancing Energy Management System for a Hybrid Wind Solar Battery Based Standalone Microgrid

Enhancing Energy Management System for a Hybrid Wind Solar B...

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2023 IEEE International Conference on Environment and electrical engineering and 2023 IEEE Industrial and Commercial Power systems Europe, EEEIC / I and CPS Europe 2023

作者： Aghmadi, Ahmed Hussein, Hossam Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798350347432

This paper introduces a highly efficient energy management system for a microgrid that combines PV system, wind turbine, and battery. The study presents an effective energy management system specifically designed for a small-scale hybrid microgrid, focusing on the development of solar and wind energy conversion systems and battery storage systems. Power electronic converters and control algorithms are implemented to evaluate the microgrid's operation. The energy management system plays a crucial role in maintaining power balance amidst varying renewable energy generation and load demand conditions. The microgrid is a testing platform to evaluate control algorithms, energy management systems, and various test scenarios. It provides a controlled environment for assessing the performance and efficiency of these systems. The efficient energy management system comprises photovoltaic (PV) modules, wind turbines, and batteries. The proposed strategy effectively manages the switching between the PV panel and the battery storage system while prioritizing power generation from the wind turbine. The efficacy and success of this strategy in microgrid control under various operational circumstances are demonstrated through MATLAB simulation results. © 2023 IEEE.

关键词： Wind power

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Dynamic Pulsed Load Mitigation in PV-Battery-Supercapacitor systems: A Hybrid PI-NN Controller Approach

Dynamic Pulsed Load Mitigation in PV-Battery-Supercapacitor ...

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2023 IEEE Design Methodologies Conference, DMC 2023

作者： Aghmadi, Ahmed Ali, Ola Hussein, Hossam Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798350315547

DC microgrids are becoming more and more popular, however there are still difficulties involving ongoing instability that are mostly caused by imbalances in energy supply and demand, particularly in situations with pulse load or variable pulse load patterns. Innovative solutions are required since these disruptive load dynamics significantly decrease the effectiveness of conventional PV-Battery control systems. conventional Proportional-Integral (PI) controllers, although widely employed, may encounter limitations when confronted with the unique challenges posed by specific load patterns, notably pulse load scenarios. These dynamic load profiles, characterized by rapid and unpredictable changes. The inherent non-linearity and variability in such load conditions can result in suboptimal control performance, potentially leading to voltage instability and transients within the microgrid. To overcome these issues and improve control performance, the introduction of Neural Network (NN) controllers promises to be a potential approach. NN controllers have a remarkable capacity to learn and adapt from data, making them particularly well-suited for situations characterized by non-linear and dynamic load behavior. In this study, a hybrid PI-NN (Proportional-Integral Neural Network) controller is introduced to reduce load effects, especially pulsed loads, in PV systems with batteries and supercapacitors. This method efficiently optimizes energy storage. For voltage control, it utilizes a PI system, which divides the reference current into low and high-frequency components for battery and supercapacitor control. For enhanced sensitivity and dynamic responsiveness, neural network control replaces conventional PIs. The performance of the hybrid PI-NN controller is evaluated in this work, with an emphasis on its potential to improve PV system efficiency in severe load circumstances. © 2023 IEEE.

关键词： Supercapacitor

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Stochastic Characterization-Based Performance Analysis of an Emulated Communication Network for Cyber-Physical Shipboard Power systems

Stochastic Characterization-Based Performance Analysis of an...

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2023 IEEE Electric Ship Technologies Symposium, ESTS 2023

作者： Abdelrahman, Mahmoud S. Nguyen, Tung-Lam Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9781665465151

Emerging advanced and innovative Information and Communication Technologies (ICT), automation strategies, and associated algorithms in the traditional power system have transformed it into a Cyber-Physical Power System (CPPS). Energy management and control are crucial in the Shipboard Power System operation. For instance, to meet the ship's energy and other ancillary demands, especially the mission-critical loads that require practical and secure network communication. Therefore, a comprehensive modeling and testing and validation approach was developed in this paper. This enables flexible system-level aspect evaluation through numerous experiments, including virtual, real, and mixed lab settings. This paper presents a scalable and flexible three-layer cyber-physical co-simulation platform implemented in the FIU smart grid testbed. This includes real-time power system simulation using OPAL-RT, ns3 for communication network emulation, and MATLAB/SIMULINK for implementing various applications. To demonstrate the platform's effective operation, energy management with a central controller for SPS was configured and implemented to test the communication network performance by creating tools to characterize the network latency for this application. © 2023 IEEE.

关键词： Ships

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Advanced Spatio-Temporal Froth Analysis Using Smart Soft Sensors in Mineral Processing

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SN computer Science 2024年第4期5卷 363页

作者： Bendaouia, Ahmed Abdelwahed, El Hassan Qassimi, Sara Boussetta, Abdelmalek Benzakour, Intissar Amar, Oumkeltoum Chekroun, Mohamed Hasidi, Oussama Lachihab, Oussama Computer Systems Engineering Laboratory (LISI) Cadi Ayyad University Marrakech Morocco SEIA Department Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Rabat Morocco R & amp D and Engineering Center Reminex Managem Group Marrakech Morocco Computer and Systems Engineering Laboratory (L2IS) Cadi Ayyad University Marrakech Morocco

In the transformative field of mineral processing, the need for innovative technologies to overcome inherent difficulties and a critical shortage of high-quality data is an acute challenge. This study addresses these pressing issues by leveraging advanced spatio-temporal deep learning techniques, specifically Convolutional Long Short-Term Memory (ConvLSTM). Focused on the Zinc flotation circuit at CMG Managem group in Morocco, our comprehensive approach encompasses meticulous data collection from a real-world industrial setting, rigorous spatial and temporal analyses, practical and accurate data augmentation, and the development of a ConvLSTM model for precise prediction of mineral grades. By capturing the temporal intricacies of froth behavior through video data, we gain insights into mineral concentration fluctuations, a critical aspect of traditional analysis. By offering a comprehensive solution that combines cutting-edge technology, meticulous data analysis, and practical augmentation methods, we aim to elevate not only mineral processing efficiency but also a broader spectrum of resource utilization and sustainable practices. This study offers a promising solution to elevate mineral processing efficiency and accuracy in the face of data limitations. It underscores the potential for transformative impacts on mineral processing operations, paving the way for more effective resource utilization and sustainable practices. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Data augmentation Industrial data analysis Machine learning Mineral processing

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Enhancing Solar Radiation Forecasting with Hybrid Ensemble Empirical Mode Decomposition and Machine Learning Techniques

Enhancing Solar Radiation Forecasting with Hybrid Ensemble E...

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2023 IEEE International Conference on Environment and electrical engineering and 2023 IEEE Industrial and Commercial Power systems Europe, EEEIC / I and CPS Europe 2023

作者： Aghmadi, Ahmed Mohammed, Osama Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798350347432

The importance of short-term solar radiation forecasting for power system use and management cannot be overstated. However, Non-stationarity and unpredictability make accurate forecasting difficult. Time series approaches are suitable for forecasting stationary time series derived from a non-stationary sequence. Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) are time-domain decomposition methods used to separate the components of the original solar radiation time series that have distinct time1-scale characteristics. As a result, the components are forecasted using the Back Propagation Neural Network (BPNN) model, which is a simple and effective machine learning method. This paper presents a hybrid EMD/EEMD-BPNN model for predicting short-term solar irradiance. To identify unique data information at different time scales, EMD/EEMD first breaks up the solar radiation time series into several stationary or fundamental sub-series. The next step is to create BPNN models with specified parameters for each subsequence to forecast new ones. Finally, each subsequence's projected value is combined to generate the final forecast result. The accuracy of solar forecasts has greatly increased, especially when utilizing hybrid methods. Furthermore, using the proposed hybrid technique for multistep forecasting resulted in even more improvement. The basic BPNN model for 15 min time step achieves predicting with a root mean square error (RMSE) of roughly 416.04 W/m2 for 15min;however, this error decreases to 65.25 W/m2 with the EMD-Hybrid Model, and 32.86 W/m2 with the EEMD-Hybrid Model. In addition, the results of the skill score have proven clearly that EMD/EEMD-BPNN Model performs better compared to typical BPNN using several meteorological inputs © 2023 IEEE.

关键词： Empirical mode decomposition

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Extrinsic and Temporal Calibration of Automotive Radar and 3-D LiDAR in Factory and On-Road Calibration Settings

IEEE Open Journal of Intelligent Transportation Systems

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IEEE Open Journal of Intelligent Transportation systems 2023年 4卷 708-719页

作者： Lee, Chia-Le Hou, Chun-Yu Wang, Chieh-Chih Lin, Wen-Chieh Institute of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan National Yang Ming Chiao Tung University Department of Electrical and Computer Engineering Hsinchu300 Taiwan Industrial Technology Research Institute Mechanical and Mechatronics Systems Research Laboratories Hsinchu31040 Taiwan National Yang Ming Chiao Tung University Department of Computer Science Hsinchu300 Taiwan

While automotive radars are widely used in ADAS and autonomous driving, extrinsic and temporal calibration of automotive radars with other sensors is still daunting due to the sparsity, uncertainty, and missing elevation angles of automotive radar measurements. We propose a target-based calibration approach of 3D automotive radar and 3D LiDAR that performs extrinsic and temporal calibration in both factory and on-road settings. In factory calibration settings, a map is built with precise target poses;target trajectories are estimated based on map-based target localization in which the accuracy of both nearby and faraway target pose estimates can be ensured. The spatial and temporal relationships between radar and LiDAR measurements are established with target trajectories to accomplish extrinsic and temporal calibration. The proposed data collection procedure provides sufficient motion for analyzing time delay between sensors and can significantly reduce the data collection effort and time. There is 52.3% distance error reduction after time delay compensation in the experiment, which shows the improvements of temporal calibration. In on-road calibration settings, the metal objects with semantic labels, such as traffic signs, are selected as calibration targets. Although there could be insufficient correspondences to infer the missing dimension of planar radar for six DoF extrinsic calibration as demonstrated in factory calibration settings, the three extrinsic parameters and the time delay are shown still to be accurate. We validated the proposed method using the nuScenes datasets, which provide sensor measurements, poses, and HD map. With twenty-two data logs, each has over 1000 correspondences, the result of extrinsic parameters reaches centimeter-level accuracy compared with the offered benchmark. The time delay compensation improves 1 meter error for radar tracking in a 20 m/s vehicle case and improves mapping quality in real world data. © 2020 IEEE.

关键词： Calibration

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