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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Wang, Baonan Wang, Hui Zhang, Dan College of Computer Science and Technology Shanghai University of Electric Power Shanghai China State Key Laboratory of Power System Operation and Control Dept. of Electrical Engineering Tsinghua University Beijing China Institute of Logistic Science and Engineering Shanghai Maritime University Shanghai China

ISBN: (纸本)9789819608966

Current optimization methods for microgrid scheduling face issues such as insufficient precision in energy distribution, high operational costs, and inefficiency. In response to these challenges, an optimization scheduling method for multi-energy microgrids based on the QUBO (Quadratic Unconstrained Binary Optimization) quantum computing model is proposed in this paper, alongside a discretization approach based on a grid partitioning strategy. To validate the feasibility of addressing microgrid optimization scheduling problems in a quantum computing environment, a QUBO model is constructed and simulation studies are conducted in the qbsolv environment provided by D-Wave. The results indicate that operational costs are significantly reduced with an increase in the number of grids, particularly a reduction of 4.52% when the number of grids increases from five to ten. This method not only effectively enhances the precision of electricity supply and energy utilization efficiency but also reduces unnecessary electrical waste and economic costs. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Microgrids

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Monarch Butterfly Optimization Algorithm for Human-Robot Collaboration Multi-Objective Disassembly Line Balancing Problem

Monarch Butterfly Optimization Algorithm for Human-Robot Col...

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2024 International Conference on Cyber-Physical Social Intelligence, ICCSI 2024

作者： Wang, Haokun Guo, Feng Guo, Xiwang Wang, Jiacun Qin, Shujin Tang, Ying Liaoning Petrochemical University Artificial Intelligence and Software Fushun China Liaoning Petrochemical University Information and Control Engineering Fushun China Monmouth University Computer Science and Software Eng. NJ United States Shangqiu Normal University Logistics Management Shangqiu China Rowan University Electrical & Computer Engineering GlassboroNJ United States

ISBN: (纸本)9798350376739

Efficient end-of-life products disassembly is crucial in the remanufacturing process. However, hazardous and repetitive disassembly tasks raise labor costs and decrease safety and efficiency. This work proposes an innovative disassembly algorithm that is inspired by monarch butterfly, aiming at improving disassembly efficiency through the utilization of human-robot collaboration in the context of a hybrid disassembly line for repetitive or hazardous tasks. The model in this paper provides the basis of solving the multi-objective problem and the mixed integer programming problem. The purpose is to improve the profit in the human robot cooperation environment, and reduce the standby time of the workstation as much as possible. Comparison of this algorithm with other intelligent optimization algorithms with experiments shows its competitive performance in both profit and idle time. © 2024 IEEE.

关键词： Profitability

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Domain Adversarial Interaction Network for Cross-Domain Fault Diagnosis 4th

Domain Adversarial Interaction Network for Cross-Domain Fau...

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Lu, Weikai Chen, Jian Zheng, Hao Fan, Haoyi Wei, Eng Yee Cao, Xinrong Zhang, Deyang School of Electronic Electrical Engineering and Physics Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China School of Computer Sciences Universiti Sains Malaysia Penang11800 Malaysia Henan Provincial Institute of Scientific and Technical Information Zhengzhou450003 China

ISBN: (纸本)9783031200984

Intelligent fault diagnosis has been widely used in the industry and plays a crucial role in the health management of machinery. In recent years, unsupervised domain adaptation (UDA) has been applied to fault diagnosis, showing excellent performance under variable working conditions. However, most existing UDA-based methods do not consider the temporal relations in the fault signal, resulting in sub-optimal performance. In this paper, we proposed a domain adversarial interaction network (DAIN) to solve this problem. By downsampling sub-sequences of fault signals and interacting with their features, DAIN can obtain feature representations containing the temporal relations. In addition, domain adversarial learning and maximum mean discrepancy (MMD) are applied to DAIN to align the domain discrepancy and distribution discrepancy of source and target domains. We conducted extensive experiments on the public Paderborn University (PU) dataset, and the results demonstrate that the proposed method can achieve higher cross-domain fault diagnosis accuracy than the existing methods. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Failure analysis

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Velocity Pausing Particle Swarm Optimization based PID controller Design for Isolated AC Microgrid 3

Velocity Pausing Particle Swarm Optimization based PID Contr...

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3rd IEEE International Conference on Smart Technologies for Power, Energy and control, STPEC 2023

作者： Kumar, Anil Altaf, Aatif Kumar, Mahendra Alhussainy, Abdullah A. Alghamdi, Sultan Alobaidi, Abdulraheem H. Dr. B R Ambedkar National Institute of Technology Jalandhar Instrumentation and Control Engineering Department Punjab Jalandhar144008 India King Abdulaziz University Faculty of Engineering Department of Electrical and Computer Engineering Jeddah21589 Saudi Arabia

ISBN: (纸本)9798350304732

The work addresses PID control design based on the velocity-pausing particle swarm optimization (VPPSO) technique. The suggested control design is utilized to develop a load frequency control (LFC) approach for an isolated microgrid (MG) with heat-pumps (HPs) and electric-vehicles (EVs). The efficiency and effectiveness of suggested control design are assessed when there are randomized solar power and load-demand disturbances. Furthermore, the robustness and effectiveness of suggested control schemes are evaluated under uncertainty in system parameters and different EVs & HPs controller's operating time-scheduling situations. The simulation results demonstrated the efficiency and usefulness of the recommended VPPSO-PID control strategy under several practical situations. © 2023 IEEE.

关键词： Electric Vehicles Load frequency control (LFC) Microgrid PID controller Velocity Pausing PSO (VPPSO)

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A Case of Cups and a Ball: Utilizing Generative Artificial Intelligence for Human-robotic Collaboration in Task Execution

A Case of Cups and a Ball: Utilizing Generative Artificial I...

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2024 International Automatic control Conference, CACS 2024

作者： Khoirurizka, Nurdin Prajogo, Joy Chrissetyo Perkins, Spencer Kuo, Chao-Hsiang Lin, Hsien-I National Yang Ming Chiao Tung University College of Electrical and Computer Engineering Hsinchu Taiwan National Yang Ming Chiao Tung University Hsinchu Taiwan National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering Hsinchu Taiwan

ISBN: (纸本)9798350354904

Within the domain of robotics, effective interaction between a human collaborator and robot is a topic of great importance. With the continued advancements in Generative Artificial Intelligence (GAI), we propose a prototype system that utilizes GAI and seeks to bridge the gap between the human and robot. This prototype utilizes a Large Language Model (LLM) combined with a vision system for detection and tracking, to allow the GAI system to control a robotic arm and manipulate objects within the action space. We model the action space within our experiments on the 3-cup Monte game where the user can prompt the system to manipulate the cups within the action space based on the ball's location. Experimentation is done on prompts of varying lengths of sequences, and we evaluate our system based on its ability to understand the prompt and correctly execute the desired task. With this collaboration of techniques and technologies, we hope to open the possibilities and extend human and robotic collaboration into new areas. The results of our experiments show promising results to this end. © 2024 IEEE.

关键词： Intelligent systems

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Virtual Synchronous Generator Droop control for Renewable Energy Sources

Virtual Synchronous Generator Droop Control for Renewable En...

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2024 IEEE Global Energy Conference, GEC 2024

作者： Cakmak, Fevzi Aykat, Sukru Kazanbaş, Mehmet Cemil Akgul, Sabahattin Department of Electricity and Energy Mardin Atuklu University Mardin Turkey Department of Computer Engineering Mardin Atuklu University Mardin Turkey Department of Control and Automation Engineering Yildiz Technical University Istanbul Turkey Department of Handicrafts Mardin Atuklu University Mardin Turkey

ISBN: (纸本)9798331532611

The connection of large-scale RES (renewable energy source) to the grid and the increase in the efficiency of energy production also causes different power quality problems. It has become mandatory for these inverter-based systems to participate in load frequency control. For this purpose, the design and simulation of a virtual synchronous generator (VSG), which enables RES to operate like synchronous generators, has been carried out in Matlab/Simulink environment. It is observed that the VSG keeps the load frequency stable according to different load conditions. ©2024 IEEE.

关键词： Synchronous generators

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Enhanced YOLOv8-Based Small Object Detection in Unmanned Aerial Vehicle (UAV) Perspective 14th

Enhanced YOLOv8-Based Small Object Detection in Unmanned Ae...

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14th International Conference on computer engineering and Networks, CENet 2024

作者： Li, Jiawen Yang, Chuxi Xu, Yi School of Computer Science and Technology Dalian University of Technology Dalian116081 China School of Control Science and Engineering Dalian University of Technology Dalian116081 China

ISBN: (纸本)9789819640157

Currently, unmanned aerial vehicles (UAVs) have been extensively utilized in ground target capture tasks, accompanied by the challenge of detecting and identifying small objects in UAV-captured images. Moreover, UAV-captured images exhibit varying scales of objects, posing additional difficulties for object detection tasks. To address these challenges, we propose an enhanced algorithm based on YOLOv8. In our algorithm, we incorporate Omni-dimensional Dynamic Convolution (ODConv) into the C2f module and apply this newly designed module to the backbone of YOLOv8. This integration enables us to leverage the advantages of ODConv, which features dynamic filters across multiple dimensions. This modified backbone reduces the model’s inference time while simultaneously enhancing prediction accuracy. Additionally, we introduce a novel Small Object Detection Structure (SODS) specifically designed for small object tasks. SODS focuses on small object regions at larger feature scales, resulting in the improvement of detection accuracy of small objects. Our proposed algorithm has been evaluated on the common unmanned aerial vehicles view datasets, and the experimental results reveal a significant improvement in both mAP and Recall values. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Drones

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An Entropy-Integrated Adaptive Coding and Scheduling Framework for Optimized Data Transmission in Fog-Cloud IoT Architectures

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IEEE Internet of Things Journal 2025年

作者： Lu, Yang Zang, Yuting Bian, Ziyi Zhao, Shuai Zheng, Yan Northeast Forestry University College of Computer and Control Engineering Harbin China Harbin Normal University College of Computer and Information Engineering Harbin China La Trobe University School of Computing Engineering and Mathematical Sciences MelbourneVIC Australia

Entropy-driven network coding has been used as a basis for optimizing data transmission and enhancing resource utilization in Fog-Cloud IoT architectures, including applications in smart cities, industrial automation, environmental monitoring, and healthcare. In Fog-Cloud IoT architectures, conventional data transmission protocols are inefficient because they cannot adapt to dynamic entropy levels, resulting in underutilized bandwidth, increased latency, and higher energy consumption. In this paper, we propose an Enhanced Entropy-Driven Network Coding (E-EDNC) framework to address these problems. Our framework integrates real-time entropy estimation with adaptive coding strategies and employs a hybrid evolutionary-reinforcement learning (HE-RL) algorithm to dynamically optimize coding parameters and scheduling decisions. Experimental results demonstrate that E-EDNC improves bandwidth utilization by 25%, reduces latency by 25%, and decreases energy consumption by 12%, thereby enhancing overall data transmission efficiency and reliability in Fog-Cloud IoT environments. © 2014 IEEE.

关键词： Network coding

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Dynamic Curing and Network Design in SIS Epidemic Processes 63

Dynamic Curing and Network Design in SIS Epidemic Processes

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Yi, Yuhao Shan, Liren Pare, Philip E. Johansson, Karl H. Sichuan University Institute of Clinical Pathology West China Hospital College of Computer Science Chengdu China Toyota Technological Institute at Chicago United States Purdue University School of Electrical and Computer Engineering West LafayetteIN United States Kth Royal Institute of Technology and They Are Also Affiliated with Digital Futures Division of Decision and Control Systems School of Electrical Engineering and Computer Science StockholmSE-100 44 Sweden

ISBN: (纸本)9798350316339

This paper studies efficient algorithms for dynamic curing policies and the corresponding network design problems to guarantee fast extinction of epidemic spread in a Markov process-based susceptible-infected-susceptible (SIS) model. We provide a computationally efficient curing algorithm based on the curing policy proposed by Drakopoulos, Ozdaglar, and Tsitsiklis (2014). Since the corresponding optimization problem is NP-hard, finding optimal policies is intractable for large graphs. We provide approximation guarantees on the curing budget of the proposed dynamic curing algorithm. To avoid the waiting period included in the original curing policy, we study network design problems to reduce the total infection rate by deleting edges or reducing the weight of edges. To this end, we provide algorithms with provable guarantees. In summary, the proposed curing and network design algorithms together provide an effective and computationally efficient approach that mitigates SIS epidemic spread in networks. © 2024 IEEE.

关键词： Markov processes

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Optimal Operation Strategy of Microgrid Based on TD3 Algorithm 7

Optimal Operation Strategy of Microgrid Based on TD3 Algorit...

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7th IEEE International Conference on Power and Renewable Energy, ICPRE 2022

作者： Cui, Chenyu Dong, Ze North China Electric Power University Hebei Technology Innovation Center of Simulation and Optimized Control for Power Generation School of Control and Computer Engineering Baoding China

ISBN: (数字)9781665450638

ISBN: (纸本)9781665450638

It is necessary to optimize the operation of micro power grid in order to improve its economy. Firstly, the mathematical model of optimal dispatching of microgrid is established. Taking the internal battery charge and discharge power, fan and photovoltaic output power of microgrid as the optimization vector and the minimum operation cost of microgrid as the optimization objective, based on the day ahead prediction data, the day is divided into 24h as a dispatching period for optimization. The Twin Delayed Deep Deterministic policy gradient algorithm (TD3) is used to solve the problem, and the power supply composition and cost data are obtained. The simulation results verify the effectiveness of the algorithm and optimal scheduling strategy. © 2022 IEEE.

关键词： Reinforcement learning

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