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A New Single-Phase Dual-Mode Active Neutral Point-Clamped Five-Level Inverter for Renewable Applications 3

A New Single-Phase Dual-Mode Active Neutral Point-Clamped Fi...

引用

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

作者： Kirubakaran, A. Barzegarkhoo, R. Liserre, Marco National Institute of Technology Warangal Department of Electrical Engineering Warangal India Kiel University Chair of Power Electronics Kiel Germany

ISBN: (纸本)9798350349207

The paper presents a new single-phase Dual-Mode Active Neutral Point-Clamped Five-Level (ANPC-5L) inverter for Renewable applications. It overcomes the shortcoming of ANPC multilevel converters proposed in the recent literature such as excessive voltage stress on devices, utilization of half the dc-link voltage and the requirement of larger than double the dc-link voltage as compared to the grid peak voltage. Therefore, in this paper, a dual-mode ANPC converter is presented which promises the merits of reduced device stress over a wide range of dc input voltages for grid connected operation. The proposed topology is designed with standard T-Type modules using 10 power devices and four dc-links and has the features of bidirectional power flow with an integrated flying capacitor (FC) technique. Moreover, it can be operated in two distinct modes such as boost mode and buck mode for a wide range of the input voltage. Simple level-shifted/phase-shifted pulse width modulation scheme is used for both the boost and a buck mode operation to realize the five-level output voltage waveform. A simple proportional-resonant (PR) controller is developed to study the dynamic response of the system under input voltage and their modes of operation using MATLAB/PLECS software and their results are presented. Finally, a detailed comparison is made with the recent ANPC-5L inverter topologies to highlight the merits of the proposed topology. © 2024 IEEE.

关键词： Pulse width modulation

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Multiscale Computational Roughness Analysis of InGaAs Growth Process for Solar Cell Applications

Multiscale Computational Roughness Analysis of InGaAs Growth...

引用

international conference on electrical engineering, computing science and automatic control (CCE)

作者： C. Rodríguez C. Camas D. Valencia I. Zúñiga H. Vilchis Instituto de Investigación e Innovación en Energías Renovables UNICACH Tuxtla Gutiérrez México Ingeniería en Energía Universidad Politécnica de Chiapas Suchiapa México

ISBN: (数字)9798350377545

ISBN: (纸本)9798350377552

In this work, we analyzed the interactions between indium gallium arsenide (In-Ga-As) atoms via Molecular Dynamics (MD) for the growth of thin films through evaporation methods with applications in tandem solar cells. In addition, film roughness and its influence on device performance were determined using the Silvaco ATLAS software. To optimize the growth conditions, we used the MD method with the open-access code LAMMPS to reproduce the thermodynamic phenomena that occur during deposition. We built different models in agreement with the information found in repositories for the interatomic Tersoff potentials of As, Ga, and In. Subsequently, we obtained the film roughness at different stages of the process and performed an electrical stimulation of the tandem solar cell. As part of the results, we obtained long deposition interactions at different temperatures and density flux. In the electrical simulation using Silvaco Atlas, the rms (root-mean-square roughness) values of film growth for models 1 and 2 revealing that Model 2 achieved an efficiency of 19.84%, higher than the 16.79% efficiency of Model 1.

关键词： Performance evaluation Photovoltaic cells Computational modeling Process control Atoms Indium gallium arsenide Surface roughness Numerical models Rough surfaces Optimization

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IoT-Based Hyper-Redundant Robot for Generating Various Snake Gait 7th

IoT-Based Hyper-Redundant Robot for Generating Various Snake...

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7th international conference on Smart Trends in computing and Communications, SmartCom 2023

作者： Megalingam, Rajesh Kannan Maruthababu, Ragavendra B. Mohandas, Sreekanth M. Manoharan, Sakthiprasad Kuttankulangara Nair, S. Anju Latha Motheram, Manaswini Department of Electronics and Communication Engineering Amrita Vishwa Vidyapeetham Amritapuri India Electrical Engineering at University of Twente Enschede Netherlands

ISBN: (纸本)9789819907687

This work proposes the idea of controlling a hyper-redundant robot in an uncomplicated method. Here, the robot used is a linkage of several Dynamixel servo actuators, which will control the motion of each joint in the robot body. As higher the degree of freedom, the higher the complexity of controlling the robot. Mathematical computation makes a major impact in the sense of controlling a robot, commonly in a higher degree of freedom robot. IoT plays a major role in controlling and manipulating objects in the physical world. It leads to the rapid growth of technologies that brings a better solution to control the robot remotely. As control is cloud computing, it has the advantage of rapid deployment and automatic software integration with robots. Much open-source firmware is available. In this paper, NODEMCU is used as a communication and controlling component for the robot, to show the effectiveness of implementing IoT in robot control. The used firmware should be Wi-Fi enabled and communicated through the mobile app. The different movements of the snake will be impended to observe the robot’s capability. As a result, the work proposed will conclude with an efficient way to control a complex robot in a demanding situation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Robots

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An MDP-based Method for Dynamic Workforce Allocation in Bernoulli Serial Production Lines 19

An MDP-based Method for Dynamic Workforce Allocation in Bern...

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19th IEEE international conference on Automation science and engineering, CASE 2023

作者： Tu, Jiachen Zhang, Liang University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States

ISBN: (纸本)9798350320695

With the development of Industry 4.0 in manufacturing, new technologies such as big data analytics, artificial intelligence, and cloud computing, have been widely deployed to production practice for performance evaluation and analysis. These technologies enabled fast and accurate production decision-making on the factory floor. To further support these activities, it's essential to develop real-time automated decision-making mechanisms backed by rigorous control and optimization analytics. The focus of this paper is on enhancing the throughput of production processes through the control and optimization of the floating workforce resources on the factory floor. Specifically, we consider serial production lines with finite buffers and machines characterized by the Bernoulli reliability model. Additionally, we assume that multiple shared workforce units can be allocated dynamically during production via real-time production bottleneck identification and mitigation in order to improve steady-state throughput. This paper addresses this problem for three and four-machine line cases, where two shared workforce units are dynamically allocated among the machines. An optimal control policy is derived based on the Markov decision process (MDP) approach. Numerical experiments are carried out to demonstrate the efficacy of the proposed method. © 2023 IEEE.

关键词： Data Analytics

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Industrial Automation Home-Lab (IAH-Lab) for Teaching/Learning During Covid-19 Pandemic 15th

Industrial Automation Home-Lab (IAH-Lab) for Teaching/Learni...

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15th APCA international conference on automatic control and Soft computing (controlO)

作者： Palma, Luis Brito Antunes, Rui Azevedo Gil, Paulo NOVA Sch Sci & Technol Caparica Portugal Polytech Inst Setubal ESTSetubal Setubal Portugal Ctr Technol & Syst Uninova Caparica Portugal

ISBN: (纸本)9783031100475;9783031100468

Covid-19 pandemic has led to temporary disruptions to face-to-face teaching/learning at universities and other institutions, and a general shift to online or hybrid education and training. In this paper, the authors propose a new pedagogic methodology for teaching and learning based on a remote industrial automation laboratory located in the teacher's house, to which it was given the acronym IAH-Lab. The main contributions are the proposed remote teaching/learning methodology, the architectures, and new remote setup (IAH-Lab) mounted for this purpose. Simulations and experimental results elucidate the potential and performance of the proposed remote laboratory (IAH-Lab).

关键词： Industrial automation and control Remote laboratory Distance education Simulation Covid-19 pandemic

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E-CVP-MVSNet: Effective Hierarchical Multi-View 3D Reconstruction Based on Light-Weight Network 5

E-CVP-MVSNet: Effective Hierarchical Multi-View 3D Reconstru...

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5th international conference on Robotics, Intelligent control and Artificial Intelligence, RICAI 2023

作者： Zhang, Xin Huang, Hongbo Lu, Lu Yan, Xiaoxu Bao, Zhongman Zhao, Qisheng Gong, Meihui Mechanical Electrical Engineering School Beijing Information Science and Technology University Beijing China Computer School Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9798350357950

Multi-view stereo based on cost volume pyramid has achieved good results in depth inference using high-resolution images. However, most approaches require a lot of computing resources, in part because convolutional layers extract redundant features and pay too much attention to some unwanted feature information. In this work, we propose a pyramid network for feature extraction that is both effective and efficient. There are two main mechanisms in the proposed approach. An effective convolution module called SCConv (Spatial and Channel reconstruction Convolution) to reduce duplicate features and encourage representative feature learning. To encode spatial data and processes high-resolution photos more efficiently, Conv2Former is also introduced into the model to enhance feature extraction capabilities. Experiments show that our method can obviously decrease the parameters, complexity and computational costs, thus improve the performance and generative ability remarkably. © 2023 IEEE.

关键词： Attention mechanism Convolution Depth estimation Feature extraction Multi-view stereo

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Improving Data Transmission Efficiency in UAV Networks Through Adaptive Coding 7

Improving Data Transmission Efficiency in UAV Networks Throu...

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7th international Youth conference on Radio Electronics, electrical and Power engineering, REEPE 2025

作者： Safadi, Majd M. Amoursky, Vladislav B. Mathematical and Software of Computing Systems Complexes and Computer Networks Faculty of Information Science and Control Systems Bauman Moscow State Technical University Moscow Russia

ISBN: (纸本)9798331531836

In recent years, unmanned aerial vehicles (UAV) have become widely used in civil and military applications such as surveillance, data collection, and cargo delivery. With the increasing use of this technology, there is a need for improved communication systems to ensure reliable and efficient data transmission. UAV networks face unique challenges due to dynamic motion, environmental interference, and energy and bandwidth limitations. The objective of this study is to propose an adaptive coding scheme using Rate-Compatible Punctured Coding (RCPC) technology, which assigns different coding rates to different data depending on their importance and channel conditions. The proposed scheme includes a mechanism to dynamically adjust the coding rates based on the change in link quality. This study demonstrates that adaptive coding can improve resource efficiency, reduce latency, and enhance communication reliability. © 2025 IEEE.

关键词： Drones

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An Efficient Detection and Classification of Plant Diseases using Deep Learning Approach

An Efficient Detection and Classification of Plant Diseases ...

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2023 international conference on Evolutionary Algorithms and Soft computing Techniques, EASCT 2023

作者： Jagadeesan, S. Deepakraj, E. Ramalingam, Venkadeshan Venkatachalam, Ilayaraja Vivekanandan, Manojkumar Manjula, R. Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India University of Technology and Applied Sciences - Shinas Branch Information Technology Department Oman Vellore Institute of Technology School of Computer Science and Engineeing Vellore India School of Engineering and Applied Sciences Srm University-AP Department of Computer Science & Engineering Andhra Pradesh Amaravati India Srm Institute of Science and Technology College of Engineering and Technology Department of Computing Technology Kattankulathur India

ISBN: (纸本)9798350313413

Crop failure caused by disease-causing pests is an important problem. Farmers struggle with disease management and detection due to inadequate interventions. The goal is to create an automatic system to efficiently identify plant diseases from photos while reducing crop losses and increasing productivity. Machine learning algorithms offer a faster and cheaper alternative to visual inspection by experts. The main goal is to perform image analysis for early diagnosis and effective disease control. The use of CNN architecture for plant disease classification and detection offers a promising solution for plant health monitoring and risk mitigation. Given the threats to crop productivity and global food security, reliable methods for early detection and accurate classification are essential. CNNs enable efficient analysis of vast plant image databases, enabling accurate plant disease identification with speed and accuracy. The multi-layer CNN approach extracts feature and refines the representation, facilitating accurate prediction and accurate diagnosis. Transfer learning methods accelerate system development and allow adaptation to plant disease-specific databases. Combining computer vision algorithms with CNN architecture enables real-time monitoring, early disease detection and targeted intervention, reducing yield losses and improving crop management. This approach uses AI, image analysis, and plant pathology to solve the challenges of sustainable agriculture and plant diseases. System performance is measured by various performance metrics. © 2023 IEEE.

关键词： CNN-Based Approach Error Rate Plant disease Precision ROC

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Security Issues in Software-Defined Networking (SDN) Environments 23

Security Issues in Software-Defined Networking (SDN) Environ...

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23rd RoEduNet conference: Networking in Education and Research, RoEduNet 2024

作者： Yalda, Khirota Gorgees Hamad, Diyar Jamal Tapus, Nicolae Okumus, Ibrahim Taner Politehnica University of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Erbil Polytechnic University Kurdistan Region IT Department Soran Technical College Erbil Iraq Kahramanmaras Sutcu Imam University Kahramanmaras Computer Engineering Faculty of Engineering Turkey

ISBN: (纸本)9798331540388

Software-Defined Networking (SDN) represents a significant shift in network architecture, providing exceptional programmability, flexibility, and simplified management. However, this paradigm shift introduces a unique set of security challenges that must be addressed to fully realize the potential of SDN. This paper examines the security issues in SDN environments, detailing the threats and vulnerabilities at various layers of the SDN architecture, including the control plane, data plane, and application plane. Through an extensive review of current literature, critical security challenges such as controller attacks, data plane breaches, and vulnerabilities in inter-plane communications are identified. Existing security solutions and mitigation strategies, such as authentication and authorization mechanisms, encryption techniques, and intrusion detection systems, are also explored. Furthermore, the paper discusses recent advances and emerging trends in SDN security, offering insights into ongoing research and future directions. The findings underscore the importance of robust security measures in ensuring the reliability and integrity of SDN deployments, providing a foundation for future innovation and development in this dynamic field. © 2024 IEEE.

关键词： Network intrusion

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Research on key technologies of cloud-edge collaboration in the power IoT based on computing power perception

Research on key technologies of cloud-edge collaboration in ...

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2024 international conference on Computer Graphics, Artificial Intelligence, and Data Processing, ICCAID 2024

作者： Chen, Wu State Grid Info-Telecom Great Power Science and Technology Co. Ltd. Fuzhou350101 China

ISBN: (纸本)9781510689275

In the construction process of new power systems, the concept of power cluster control has emerged with the integration of large-scale distributed new energy, and regional autonomy is an effective means of distributed new energy consumption. At present, the electric power smart IoT focuses on the collection and distribution of environmental, state, and low-voltage electrical quantities in various scenarios of transmission and distribution in quasi real-time. However, the edge IoT technology that supports distributed new energy consumption in substations and flexible coordinated control between substations is not yet perfect. The traditional processing method relying on centralized cloud platforms has poor real-time performance. The existing electric power smart IoT system has limited edge computing resources, which are difficult to meet the rapid response needs of single substation autonomy and multi substation interaction. There is an urgent need for resource collaboration on the edge and platform sides, and research on key technologies for cloud edge collaboration of electric power IoT based on computing power perception is needed to expand and improve the existing electric power smart IoT system. © 2025 SPIE.

关键词： Edge computing

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