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共 15478 条记录，以下是341-350 订阅

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Stealthy False Data Injection Cyberattack Targeting under Load Tap Changing Transformers in Smart Power Grid Causing Abnormal Voltage Profile 3

Stealthy False Data Injection Cyberattack Targeting under Lo...

引用

3rd international conference on Power, control and computing Technologies, ICPC2T 2024

作者： Naderi, Ehsan Asrari, Arash College of Engineering and Computer Science Arkansas State University Department of Electrical Engineering JonesboroAR United States Purdue University Northwest Department of Electrical and Computer Engineering HammondIN United States

ISBN: (纸本)9798350349207

In the process of protecting power systems against different types of cyberattacks, the primary step is to precisely model such frameworks from attacker's perspective. This paper investigates a false data injection (FDI) attack framework, which can target under-load tap changing (ULTC) transformers, resulting in manipulated voltage profile in radial smart distribution networks. The developed FDI model compromises the voltage profile of a distribution feeder through misleading the volt/var optimization, that optimally manages system-wide voltage profile and flow of reactive power. The presented attack model is formulated as a bi-objective optimization problem. The objective functions from the attacker's point of view are 1) minimizing the level of false data to be injected into the smart meters associated with load data and 2) maximizing the voltage deviation of the distribution grid. Negative impacts of such a cyberattack model have been validated and discussed in this work on an IEEE distribution test system, necessitating proper remedial actions, which will be elaborated in the next step of this research. © 2024 IEEE.

关键词： Reactive power

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IoT-Based Transfer Learning and Genetic Algorithm Approaches for Smart Environmental Pollution Detection and Management 5

IoT-Based Transfer Learning and Genetic Algorithm Approaches...

引用

5th IEEE international conference on Advances in electrical, computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Alauddin, Shafqat Sree Vidhya, S. Pragadeeswaran, S. Sowjanya, P. Bhokare, Rajashree Khan, Maaz Allah Shibli National College Department of Chemistry Uttar Pradesh Azamgarh India Erode Sengunthar Engineering College Department of Computer Science and Engineering Tamilnadu Thudupathi India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Cse Chennai India Department of Ece Telangana Dhulapally India Dr. D. Y. Patil Institute of Technology Department of Electrical Engineering Pimpri Maharashtra Pune India Department of Engineering & Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9798350356236

The identification of environmental pollution remains to be a significant issue, as conventional technologies lack scalability and flexibility to dynamic, real-time situations. This study presents an IoT-enabled hybrid model that combines transfer learning and genetic algorithms to overcome these restrictions. IoT networks enable real-time, extensive data acquisition, whereas transfer learning uses pre-trained models for effective feature extraction and domain adaption. Genetic algorithms enhance hyperparameters and sensor configurations, guaranteeing energy economy and optimal model performance. The suggested CNN-LSTM architecture utilising multi-scale attention attains a training accuracy of 95.6% and an F1 score of 0.96, exceeding the performance of conventional Random Forest and CNN models in accuracy, recall, and precision. The comparative study confirms the model's strength and flexibility, illustrating its capacity for scaled, practical applications. This framework creates a dependable and effective system for intelligent environmental pollution control, providing substantial improvements in detection accuracy and operational efficacy compared to current methods. © 2025 IEEE.

关键词： Environmental management

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Design and Research of automatic Generation control Code for Dual Three-Phase PMSM Based on FPGA 26

Design and Research of Automatic Generation Control Code for...

引用

26th international conference on electrical Machines and Systems, ICEMS 2023

作者： Song, Fangzheng Xu, Wei Wang, Jiyao Southeast University Software College Suzhou China Southeast University Electrical Engineering Nanjing China

ISBN: (纸本)9798350317589

This article investigates the impact of the sector control delay problem that has been commonly encountered in traditional multiphase motor control, which reduces the synchronization of motor sectors, increases the ripple amplitude, and reduces control accuracy. To address this issue, this paper proposes a new motor control method based on FPGA parallel computing and parallel control ability. By utilizing the characteristics of FPGA, this method reduces control latency and improves control synchronization. To simplify the development process of this control method, this article adopts a model design method based on HDL Coder to optimize parallel channels and reduce motor control delay time. To experimentally verify this method, a console frame is introduced as the time stamp to evaluate the running time of the algorithm. Under a dual three-phase permanent magnet synchronous motor test platform, the results convince the effectiveness of this high-performance method that can achieve synchronization for multi-phase currents with ripple. The proper configuration of the HDL toolchain is also described that provides fast development of the FPGA control model. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Convolutional Neural Network Based Approach for automatic Detection of Diseases from Pomegranate Plants 8

Convolutional Neural Network Based Approach for Automatic De...

引用

8th IEEE international conference on Distributed computing, VLSI, electrical Circuits and Robotics, DISCOVER 2024

作者： Rana, Harsh Singh Manjunatha, N. Pokhare, Somnath S. Marathe, Rajiv A. Rajan, Jeny National Institute of Technology Karnataka Dept. of Computer Science and Engineering Surathkal India ICAR National Research Centre on Pomegranate Solapur India

ISBN: (纸本)9798350350593

Recent advancements in Artificial Intelligence, particularly Convolutional Neural Networks (CNNs), have significantly enhanced computer vision tasks, including plant disease detection. India is a global leader in pomegranate cultivation and production. Pomegranate is a vital horticultural commodity with significant export potential but is highly susceptible to various diseases, leading to substantial economic losses. Existing research on automatic pomegranate disease detection has limitations, as it typically analyzes either fruits or leaves in isolation and uses datasets with plain backgrounds that do not reflect real-world complexities such as lighting variations and overlapping foliage. This study proposes a novel hybrid deep learning approach that addresses these limitations. We utilized a hybrid CNN model specifically developed using the pomegranate dataset provided by the ICAR-National Research Centre on Pomegranate. This comprehensive collection includes 1,632 high-resolution images captured from orchards across India, categorized into three classes: healthy, bacterial diseases, and fungal diseases. Our model achieves an impressive accuracy rate of 98.46%, demonstrating its potential for real-world application in pomegranate disease detection and improved agricultural outcomes. © 2024 IEEE.

关键词： Convolutional neural networks

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2nd international conference on Sustainable Technology and Advanced computing in electrical engineering, ICSTACE 2023

2nd International Conference on Sustainable Technology and A...

引用

2nd international conference on Sustainable Technology and Advanced computing in electrical engineering, ICSTACE 2023

ISBN: (纸本)9789819992348

The proceedings contain 40 papers. The special focus in this conference is on Sustainable Technology and Advanced computing in electrical engineering. The topics include: Performance Analysis of Various Converters in PV Systems Using PSO-Based MPPT;Ultra-Gain Two-Input Two-Output DC–DC Converter for Electric Vehicle Application;Modified Switched Capacitor-Based Non-isolated Bidirectional DC–DC Converter for Obtaining High VTR;wavelet-Based Quadrature Rule to Evaluating Quasi-Type Singular Integral Equations;Spherical Induction Motor—Speed control Using VFD;a Machine Learning and Fuzzy-Based Reliable Data Collection and Communication in AioT—Fog computing Environment;smart Home Energy Management with a Coordinated Neighborhood Energy Sharing;Dynamic Operation of Islanded DC Microgrid with Fuel Cell Using Hybrid Energy Storage Systems;fault Detection, Classification, and Identification of Shunt Compensated Distribution System Through Wavelet Transforms;Optimal Sizing of PV/Wind/Battery Grid-Connected Hybrid Renewable Energy Systems Using TLBO Algorithm;diagnosis of Clustered Microcalcifications in Breast Cancer Using Mammograms;Stochastic Optimal Allocation of Photovoltaic-Based DG and DSTATCOM in Distribution System Considering Uncertainties of Loads and Solar Irradiance;breast Cancer: automatic Detection from Mammogram Images by Utilizing Deep Learning Methods;Standalone Photovoltaic Fed Water Pumping System with Better Performance Using P&O MPPT Techniques;Accurate Estimation of Amplitude, Phase, and Frequency of a Sinusoidal Signal Contaminated with Harmonics and DC Decaying Components;experimental Investigation and Pollution Contaminant Severity Analysis of Glass and Porcelain Insulators Under controlled Conditions;Classification of Dry and Wet Snow of Glaciers in Western Himalayas Using SAR Polarimetric Decomposition—An Application of Satellite Image Processing;optimum Overcurrent Relay Coordination for Radial Distribution Networks Using Improved Mathematical Fo

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Mechanism design and performance analysis of tracked pipe robot 6

Mechanism design and performance analysis of tracked pipe ro...

引用

6th international conference on Robotics, Intelligent control and Artificial Intelligence, RICAI 2024

作者： Wang, Shuhai Zhang, Nanfeng Jin, Biao Li, Qingan College of Mechanical and Electrical engineering Guangdong University of Science & Technology Guangdong Dongguan523083 China

ISBN: (纸本)9798331541699

Pipeline robot is a kind of system that can automatically walk along the pipeline, with one or more sensors and operation machinery (such as manipulator, spray gun, etc.), under the remote control or automatic control of the operator, can carry out a series of pipeline operations machine-electric-instrument integrated system. It is often used in petroleum, chemical industry, nuclear industry, urban construction and other engineering pipeline quality inspection, welding, maintenance and so on. Pipeline robot is also a combination of multiple disciplines, involving mechanical engineering, automatic control, computers, sensors, artificial intelligence and electronic technology. At present, the development of pipeline robot mainly focuses on the innovation and development of mechanism, drive, sensors, intelligent control, miniaturization, power supply and communication. Based on the scientific research achievements at home and abroad, this paper systematically studied the driving principle and mode, movement principle and mechanical mechanism of the pipeline robot. Main work for the institutional research design of pipeline robots. Based on the comprehensive consideration of various factors, the pipeline robot mobile mechanism is determined, and points out the main problems that should be considered when designing the robot. © 2024 IEEE.

关键词： Nuclear industry

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CDQKL: Consensus-Based Distributed Quantum Kernel Learning 1

CDQKL: Consensus-Based Distributed Quantum Kernel Learning

引用

1st international conference on Quantum Communications, Networking, and computing, QCNC 2024

作者： Ma, Wenxuan Liu, Mengxiang Deng, Ruilong State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Zhejiang University Hangzhou310027 China University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350366778

The field of quantum computing has developed rapidly in recent years due to its promising trend of surpassing traditional machine learning in terms of speed and effectiveness. Quantum kernel learning is one of the paradigms of quantum machine learning, but the training of quantum kernel is time consuming. Therefore, this work makes the first attempt to introduce a consensus-based distributed approach to quantum kernel learning - named CDQKL - that only requires to exchange model parameter information between adjacent nodes while avoiding the need of sharing local training data. Through comparative experimental studies, the advantages of CDQKL in classification accuracy and convergence speed are verified. Considering the popularization of quantum computing cloud service and miniaturization of quantum terminals, the CDQKL adapting to this trend is able to play a vital role in data security, which implies the far-reaching significance of this work. Our code is available at https://***/Leisurivan/CDOKL. © 2024 IEEE.

关键词： Quantum computers

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Frequency control Analysis Using Modified Fractional Order PID controller 3

Frequency Control Analysis Using Modified Fractional Order P...

引用

3rd Odisha international conference on electrical Power engineering, Communication and computing Technology, ODICON 2024

作者： Mohapatra, Gayatri Jena, Tarakanta Tripathy, Sabita Jena, Narendra Kumar Sahu, Prakash Chandra Debnath, Manoj Kumar Siksha 'o' Anusandhan University Department of Electrical Engineering Odisha India Siksha 'o' Anusandhan University India Engineering Department of Electrical Odisha India School of Electrical and Comp. Science Indian Institute of Technology Bhubaneswar India

ISBN: (纸本)9798350354379

In a unified power system, frequency oscillations always pose a concern due to the unpredictability of load. These oscillations are typically mitigated by controllers. In this investigation, we projected a unique structure of the controller by modifying FOPID controllers. By utilizing the modified FOPID controller, we can enhance benefits as it offers superior control actions. This approach will assist in keeping the frequency within acceptable bounds during faults or fluctuations in demand within an interconnected power system that incorporates a geothermal power plant (GTPP), a dish-Stirling solar-thermal system (DSTS), and a conventional steam power plant (SPP). Sine-Cosine Optimization (SCO) algorithm is employed to tune the controllers, with ITAE as the evaluative or fitness function. Initially, the system's performance is assessed under a 3% Step Load Perturbation (SLP) in area 1 and compared to conventional PID and FO-PID controllers by examining negative undershoots, settling time, and positive overshoots. In the second case, the system's response is tested by increasing the load in area 1 by 5%, and the results are compared by evaluating the modified FOPID controller's performance against PID and FO-PID controllers, both tuned with the sine-cosine algorithm. The modified FOPID controller demonstrates superior performance over the other controllers. This comprehensive analysis underscores the effectiveness and reliability of the modified FO-PID controller in managing frequency oscillations and maintaining stability in a dynamic unified power system. © 2024 IEEE.

关键词： Three term control systems

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Design of Library automatic Navigation Intelligent Vehicle System Based on ROS 4

Design of Library Automatic Navigation Intelligent Vehicle S...

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4th international Signal Processing, Communications and engineering Management conference, ISPCEM 2024

作者： Zhang, Shibiao Lu, Yangyu Chen, Yuru Faculty of Mechanical and Electrical Engineering China Jiliang University Hangzhou China

ISBN: (纸本)9798331528676

This article introduces a library automatic navigation intelligent vehicle system based on ROS. The system aims to improve the management efficiency of the library and optimize the service experience for readers. The smart car uses LiDAR for environmental scanning and map construction, and achieves autonomous path planning and navigation through SLAM technology. The smart car is equipped with a robotic arm and ca7era, which can recognize and grab books, and automatically navigate to the user's location. The system uses Nvidia JETSON Orin Nano as the upper computer and STM32F407 as the lower computer, and utilizes ROS functional packages such as Gmapping and Move_base for map building, positioning, and path planning. In addition, the system also provides remote control and voice control interfaces, and incorporates safety measures to ensure the safety and reliability of the smart car during navigation. ©2024 IEEE.

关键词： Remote control

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Maximum Power Point Tracking for direct drive Wind Turbines: An Active Disturbance Rejection control approach 19

Maximum Power Point Tracking for direct drive Wind Turbines:...

引用

19th international conference on electrical engineering, computing science and automatic control, CCE 2022

作者： Aguilar-Orduna, Mario Andres Sira-Ramirez, Hebertt Jose Gomez-Leon, Brian Camilo Cinvestav-IPN Electrical Engineering Department Mexico City Mexico Cinvestav-IPN Automatic Control Department Mexico City Mexico

ISBN: (数字)9781665455084

ISBN: (纸本)9781665455084

In this article, an Active Disturbance Rejection control (ADRC) is proposed for the Maximum Power Point Tracking (MPPT) task on a Direct Drive (DD) wind turbine. The used model takes into account the flexibility of the shaft coupling the blades' rotor with the permanent magnet synchronous generator (PMSG). The proposed linear control scheme offers a high degree of robustness and good tracking performance, despite the presence of significant disturbances and the fact that a large part of the dynamics is ignored and treated as an unknown disturbance. The ADRC method also avoids measuring the entire set of phase variables of the system. Realistic digital computer simulations are provided that test the validity of the approach. © 2022 IEEE.

关键词： Wind turbines

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