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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Mathieu, Reynold Boamah, Sharon Cooper, Austin Agnew, Dennis McNair, Janise Bretas, Arturo University of Florida Department of Electrical and Computer Engineering GainesvilleFL United States Distributed Systems Group Pacific Northwest National Laboratory RichlandWA United States G2Elab Grenoble INP CNRS Universite Grenoble Alpes Grenoble38000 France

ISBN: (纸本)9798350313604

Network communication has been proven to be a very important tool and a key factor in the recent development and progress of the power grid operation. It is also considered as the foundation for the smart grid because information and communication are integrated into electricity distribution to achieve reliable and accurate knowledge of the power grid. In previous years, absorbing energy from substations and delivering it to customers was the only type of interaction we knew between utility companies and customers. Presently, the growing connections of small distributed generation units caused by the cost reduction of most of the technologies used in the generation and storage of electrical energy, along with the potential benefits of renewable energy have pushed many researchers to look into the improvement of information and communication technologies (ICT) in order to ensure a bidirectional flow of power and data. Moreover, the evolution of information and communication technologies and its applications to smart grid have converted the smart grid into a cyber-physical system where vulnerabilities and additional security challenges such as cyber-threats and cyber-attacks have emerged. Previously, we have demonstrated that using machine learning-based processing on data gathered from communication networks and the power grid was a promising solution for detecting cyber threats by implementing a co-simulation of cyber-security for cross-layer strategy. Since the majority of the challenges observed can only be solved in the network communication layer, we present in this work a physics-based state estimation model of the communication network system towards enhanced cyber-physical security of the smart grid. Information integration with the previously developed machine learning model is developed, providing an enhanced cyber-physical security application for the smart grid. Easy-to-implement model, without hard-to-derive parameters, highlights potential aspects of th

关键词： Smart power grids

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Multi-Objective Particle Swarm Optimisation for Pareto Optimal Tuning of Super-Twisting controller in Quadcopter 4

Multi-Objective Particle Swarm Optimisation for Pareto Optim...

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4th International Conference on Innovative Research in Applied Science, engineering and Technology, IRASET 2024

作者： Vera, Octavio Gomez, Victor Rodas, Jorge Kali, Yassine Saad, Maarouf Comparatore, Leonardo Universidad Nacional De Asunción Lab. Of Power And Control Systems Facultad De Ingeniería Luque Paraguay School Of Engineering Université Du Québec En Abitibi-Témiscamingue Rouyn-Noranda Canada Grepci Laboratory École De Technologie Supérieure Department Of Electrical Engineering Montreal Canada

ISBN: (纸本)9798350309508

This work introduces the Multi-Objective Particle Swarm Optimisation (MOPSO) algorithm to optimise and speed up adjusting gains of a modified super-twisting second-order sliding-mode (MSTSOSM) attitude controller designed for a quadcopter. The tuning process is executed in MATLAB/Simulink, utilising a non-linear model that incorporates the physical characteristics of the quadcopter. The optimised parameters correspond to the MSTSOSM gains associated with each attitude state. The MSTSOSM constructs vectors using the gains of each Euler angle, employing particle coordinates computed by the MOPSO algorithm. These coordinates dynamically evolve during the algorithm's execution, exploring the parameter space for optimal positions. Consequently, the Pareto front emerges, showcasing Pareto's optimal solutions. The optimisation methodology is grounded in Pareto dominance theory, evaluating performance indicators such as rise time, root-mean-square error, and overshoot across all attitude axes in step responses. This systematic approach transcends traditional trial-and-error methods, comprehensively exploring the parameter space. Simulation and experimental results affirm the efficacy of this tuning process, demonstrating its capacity to enhance quadcopter control with precision and efficiency. © 2024 IEEE.

关键词： Sliding mode control

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Efficient photoelectrochemical conversion of CO_(2)to syngas by photocathode engineering

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Green Energy & Environment 2022年第3期7卷 545-553页

作者： Sheng Chu Pengfei Ou Roksana Tonny Rashid Yuyang Pan Daolun Liang Huiyan Zhang Jun Song Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing210096China Department of Electrical and Computer Engineering McGill UniversityMontrealQC H3A 0E9Canada Department of Mining and Materials Engineering McGill UniversityMontrealQC H3A 0C5Canada

The synthesis of renewable chemical fuels from CO_(2) and H_(2)O via photoelectrochemical(PEC)route reprensents a promising room-temperature approach for transforming greenhouse gas into value-added chemicals(e.g.,syngas),but to date it has been hampered by the lack of efficient photocathode for CO_(2) ***,we report efficient PEC CO_(2) reduction into syngas by photocathode *** photocathode is consisting of a planar p-n Si junction for strong light harvesting,GaN nanowires for efficient electron extraction and transfer,and Au/TiO_(2)for rapid electrocatalytic syngas *** photocathode yields a record-high solar energy conversion efficiency of 2.3%.Furthermore,desirable syngas compositions with CO/H_(2)ratios such as 1:2 and 1:1 can be produced by simply varying the size of Au *** calculations reveal that the active sites for CO and H_(2)generation are the facet and undercoordinated sites of Au particles,respectively.

关键词： syngas photocathode photoelectrochemical

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Integration of ANN for Accurate Estimation and control in Wastewater Treatment 28

Integration of ANN for Accurate Estimation and Control in Wa...

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28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Ţiru, Andreea Elena Vasiliev, Iulian Diaconu, Larisa Vilanova, Ramon Voipan, Daniel Ratnaweera, Harsha Dunǎrea de Jos University of Galaţi Department of Automatic Control and Electrical Engineering Galaţi Romania Autonomous University of Barcelona Department of Automation Systems and Advanced Control Research Barcelona Spain Dunǎrea de Jos University of Galaţi Department of Computer Science and Information Technology Galaţi Romania Ås Norway

ISBN: (纸本)9798350339918

The management of wastewater is a significant global concern that calls for innovative solutions to lessen its negative effects on the environment. Conventional techniques of treating wastewater need improvement in order to deal with newly discovered contaminants, which highlights the importance of providing precise estimates of process performance and resource requirements. The worsening water shortage situation requires a paradigm shift in which wastewater is viewed as a useful resource. It is possible to create an economy that is both sustainable and circular by treating and recycling wastewater, putting less pressure on freshwater supplies, and leaving as little of an environmental footprint as possible. This study investigates the use of Artificial Neural Networks (ANNs) as software estimators in the treatment of wastewater, with a particular emphasis on predicting ammonium concentrations in effluent. In order to deal with imbalanced time-series data, the research introduces innovative data pretreatment strategies. These techniques include a Sliding Window protocol, Data Normalization, and a K-Fold training scheme. This illustrates the potential of ANNs to revolutionize wastewater treatment procedures and drive developments in this field. The suggested method demonstrates higher performance when estimating pollutant concentrations, showing the ability of ANNs to do so. © 2023 IEEE.

关键词： Neural networks

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Microgrid Frequency Stability: A Proactive Scheme Based on Dynamic Predictions

Microgrid Frequency Stability: A Proactive Scheme Based on D...

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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Paramo, Gian Bretas, Arturo Meyn, Sean University of Florida Department of Electrical and Computer Engineering GainesvilleFl United States G2Elab Grenoble INP CNRS Université Grenoble Alpes Grenoble38000 France Distributed Systems Group Pacific Northwest National Laboratory Richland99354 United States

ISBN: (纸本)9798350313604

The dynamic nature of microgrids introduces challenges in the context of frequency stability. This work presents a framework where the future state of microgrid frequency is predicted and corrective actions are optimized. Predictions are generated through Bayesian filters leveraging synchronized data acquired via PMUs. Taking a proactive approach makes it possible to optimize corrective actions considering dynamic system conditions. Testing is conducted via Matlab simulations. The performance of the solution presented in this work is compared to traditional load-shedding schemes and to predictive solutions found in literature. The results indicate that the proposed framework outperforms both. Some of the advantages of this framework include a reduction in amount of load dropped during compensation, the use of adaptive parameters which eliminates the need to simulate contingency conditions, and dynamic uncertainty quantification provided the particle filter. © 2024 IEEE.

关键词： MATLAB

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Explainable Application Intent for Zero-Touch Networking: An Incorporation of Hypergraph and Transformer

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IEEE Transactions on Communications 2025年

作者： Wu, Bing Zou, Sai Liwang, Minghui Ni, Wei Wang, Xianbin Guizhou University College of Big Data and Information Engineering China National Key Laboratory of Autonomous Intelligent Unmanned Systems Department of Control Science and Engineering China Tongji University Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai China Data61 CSIRO Australia Department of Electrical and Computer Engineering Western University Canada

The autonomous interpretation of application intent (APPI) represents the primary step towards achieving closed-loop autonomy in zero-touch networking (ZTN) and also a prerequisite for intent-based networking (IBN). However, understanding APPIs and invoking the corresponding network resources require network professionals with extensive technical expertise to customize network service requests (NSRs), which presents significant challenges for the large-scale deployment of ZTN. This paper investigates an interesting problem of autonomous interpretation of APPIs for ZTN, where a novel mechanism integrating hypergraph and transformer with completeness assurance (HyperTrans-CA) is proposed. In particular, we first involve the Bayesian theory to model APPIs interpretability as maximizing the correct transition probability, where hypergraph is used to describe the complex relationship between application characteristics (e.g., scenario function, and performance) and NSRs, including network devices, virtual network functions (VNFs), and resources. Then, the hypergraph is integrated into the encoder, decoder, and attention mechanisms of Transformer, and a completeness assurance mechanism is designed to improve the prediction accuracy. The convergence of HyperTrans-CA and the corresponding convergence speed of the hypergraph-boosted Transformer in the graph search process are also analyzed. Comprehensive simulations and empirical measurements regarding industrial internet demonstrate that HyperTrans-CA can effectively explain/understand APPIs. Compared to the state-of-the-art Transformer and ChatGPT3.5 models, HyperTrans-CA improves the prediction accuracy of APPIs mapped to VNFs by 23% and 46%, respectively, while raising the prediction accuracy of VNF locations by 8.6 and 17.3 times. © 2025 IEEE.

关键词： Bayesian networks

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Converse negative imaginary theorems

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Automatica 2024年 165卷

作者： Khong, Sei Zhen Zhao, Di Lanzon, Alexander Department of Electrical Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan Department of Control Science and Engineering & National Key Laboratory of Autonomous Intelligent Unmanned Systems & Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China Control Systems Centre Department of Electrical and Electronic Engineering School of Engineering University of Manchester Oxford Road ManchesterM13 9PL United Kingdom

Converse negative imaginary theorems for linear time-invariant systems are derived. In particular, we provide necessary and sufficient conditions for a feedback system to be robustly stable against various types of negative imaginary (NI) uncertainty. Uncertainty classes of marginally stable NI systems and stable strictly NI systems with restrictions on their static or instantaneous gains are considered It is shown that robust stability against the former class entails the strictly NI property, whereas the latter class entails the NI property. We also establish a non-existence result that no stable system can robustly stabilise all marginally stable NI uncertainty, thereby showing that the uncertainty class of NI systems is too large as far as robust feedback stability is concerned, thus justifying the consideration of subclasses of NI systems with constrained static or instantaneous gains. © 2024 Elsevier Ltd

关键词： Linear time-invariant system

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A Graph-Based Self-Calibration Technique for Cable-Driven Robots with Sagging Cable

A Graph-Based Self-Calibration Technique for Cable-Driven Ro...

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

作者： M. R. Dindarloo A. S. Mirjalili S. A. Khalilpour R. Khorrambakht Stephan Weiss H. D. Taghirad Advanced Robotics and Automated Systems (ARAS) Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Tandon School of Engineering Control/Robotics Research Laboratory New York University Brooklyn NY Department of Smart Systems Technologies University of Klagenfurt Austria

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

The efficient operation of large-scale Cable-Driven Parallel Robots (CDPRs) relies on precise calibration of kinematic parameters and the simplicity of the calibration process. This paper presents a graph-based self-calibration framework that explicitly addresses cable sag effects and facilitates the calibration procedure for large-scale CDPRs by only relying on internal sensors. A unified factor graph is proposed, incorporating a catenary cable model to capture cable sagging. The factor graph iteratively refines kinematic parameters, including anchor point locations and initial cable length, by considering jointly onboard sensor data and the robot’s kineto-static model. The applicability and accuracy of the proposed technique are demonstrated through Finite Element (FE) simulations, on both large and small-scale CDPRs subjected to significant initialization perturbations.

关键词： Meters Accuracy Perturbation methods Kinematics Robot sensing systems End effectors Software Calibration Sensors Finite element analysis

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Assessing the Robustness of nnU-Net in the Detection of Prostate Lesions via Bi-Parametric MRI

Assessing the Robustness of nnU-Net in the Detection of Pros...

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2023 IEEE EMBS Special Topic Conference on Data Science and engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Zaridis, Dimitrios I. Mylona, Eugenia Tachos, Nikolaos Kalantzopoulos, Charalampos Pezoulas, Vasileios C. Koutsouris, Dimitrios D. Matsopoulos, George K. Marias, Kostas Tsiknakis, Manolis Fotiadis, Dimitrios I. National Technical University of Athens School of Electrical and Computer Engineering Biomedical Engineering Laboratory AthensGR15773 Greece Forth Biomedical Research Institute Ioannina Greece University of Ioannina Ioannina Greece Forth Institute of Computer Science Heraklion Greece Hellenic Mediterranean University Department of Electrical and Computer Engineering Crete Heraklion Greece FORTH-IMBB Ioannina Greece University of Ioannina Unit of Medical Technology and Intelligent Information Systems Materials Science and Engineering Department IoanninaGR 45110 Greece

ISBN: (纸本)9798350383386

Within the scope of prostate cancer diagnostic imaging, distinguishing lesions is challenging due to their subtle appearance and the prostate gland's complexity. This study employed the nnU-Net, a state-of-the-art medical image segmentation model, on a dataset of 301 patients from 2 openly available datasets to identify whether lesion sizes are affecting the model's performance. By applying t-SNE dimensionality reduction algorithm among dice score and respective lesion sizes, we found that nnU-Net behaves differently for lesions smaller than 9mm compared to lesions larger than 15mm. These insights can inform specialized training approaches for future deep learning models in prostate lesion *** Relevance: The main contributions of this study is, to investigate whether lesion sizes affects nnU-Net's deficiency leading to the development of more specialized models in respect to these factors. © 2023 IEEE.

关键词： Urology

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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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International Conference on Environment and electrical engineering (EEEIC)

作者： Ahmed Aghmadi Hossam Hussein Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami USA

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.

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