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5th International Conference on Electronics and Communication, Network and Computer Technology, ECNCT 2023

作者： Li, Kun Gong, Zheng Meng, Jiaheng Liu, Qing Tianjin University of Technology Tianjin Key Laboratory of Film Electronic and Communication Device Tianjin China Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin China

ISBN: (纸本)9798350328660

Wireless Power Transfer (WPT) technology provides a convenient and efficient power supply solution for mobile devices. The utilization of constant current (CC) and constant voltage (CV) control in WPT systems proves valuable for charging battery applications. This paper presents a novel WPT system with CC and CV output characteristics, employing a switching topology. Specifically, the LCC-S and LCC-P topologies are applied and rigorously simulated. The proposed MCR-WPT system's output characteristics in both CC and CV modes are meticulously validated using Saber software. The simulation results distinctly demonstrate the system's capability to achieve CC and CV outputs within a varying load resistance range of 5Ω to 30Ω, thus conclusively establishing the efficacy of the topology switching technology. © 2023 IEEE.

关键词： Topology

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The Optimization Method for key control Parameters of Wind Turbines to Suppress Transient Overvoltage in Wind-Fire Bundling AC/DC Power Delivery system 4

The Optimization Method for Key Control Parameters of Wind T...

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4th International Conference on intelligent Power and systems, ICIPS 2024

作者： Liang, Zhuohang Ling, Wuneng Li, Chengxiang Liang, Zhencheng Xiong, Li Liang, Yangdou Electric Power Research Institute China Southern Power Grid Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Guangxi Power Grid Dispatch and Control Center Nanning China

ISBN: (纸本)9798331532765

This paper analyzes the causes of overvoltage in the sending-end grid due to phase-change failures in the receiving-end grid, based on the operational principles and control methods of conventional high-voltage DC transmission. It systematically examines the operational characteristics of the sending-end grid voltage during transient processes. Considering the control strategy and output power expression of direct-drive wind turbines connected to the grid, and in accordance with current control requirements for voltage transients in wind turbine units, the study identifies parameter values affecting the control performance of voltage transients. It proposes a key control parameter optimization model aimed at minimizing fluctuations in the terminal voltage of wind turbines during voltage faults, integrating a simulated annealing optimization algorithm. Detailed implementation steps for optimizing key parameters are provided. Finally, the effectiveness of the proposed method in suppressing overvoltages at the terminal of wind turbines is validated using a model built on an electromechanical transient simulation platform. © 2024 IEEE.

关键词： Simulated annealing

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Forming Circle Formations of Multi-agent systems Under Actuator Faults 5th

Forming Circle Formations of Multi-agent Systems Under Actu...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Liu, Jiajun Ru, Xinfeng Xia, Weiguo Wang, Chen China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration Shanghai China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China National Engineering Research Center of Software Engineering and the State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

ISBN: (纸本)9789811939976

A distributed fault-tolerant formation control law is designed in this paper for multi-agent systems under external disturbances and actuator faults including time-varying loss of effectiveness faults. The initial position of each agent is already on a circle and the control purpose is to form a desired formation on this circle. Based on this local information, a distributed adaptive formation control law is designed by employing the congelation of variables method to deal with time-varying actuator faults. Finally, a simulation example is given to verify the effectiveness of the adaptive fault-tolerant control design method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Scribble-Supervised Video Object Segmentation

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 339-353页

作者： Peiliang Huang Junwei Han Nian Liu Jun Ren Dingwen Zhang Brain and Artificial Intelligence Laboratory School of AutomationNorthwestern Polytechnical UniversityXi’an 710072China IEEE Department of Engagement Services Mohamed Bin Zayed University of Artificial IntelligenceAbuDhabiUnited Arab Emirate Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory BeijingChina

Recently,video object segmentation has received great attention in the computer vision *** of the existing methods heavily rely on the pixel-wise human annotations,which are expensive and time-consuming to *** tackle this problem,we make an early attempt to achieve video object segmentation with scribble-level supervision,which can alleviate large amounts of human labor for collecting the manual ***,using conventional network architectures and learning objective functions under this scenario cannot work well as the supervision information is highly sparse and *** address this issue,this paper introduces two novel elements to learn the video object segmentation *** first one is the scribble attention module,which captures more accurate context information and learns an effective attention map to enhance the contrast between foreground and *** other one is the scribble-supervised loss,which can optimize the unlabeled pixels and dynamically correct inaccurate segmented areas during the training *** evaluate the proposed method,we implement experiments on two video object segmentation benchmark datasets,You Tube-video object segmentation(VOS),and densely annotated video segmentation(DAVIS)-*** first generate the scribble annotations from the original per-pixel ***,we train our model and compare its test performance with the baseline models and other existing *** experiments demonstrate that the proposed method can work effectively and approach to the methods requiring the dense per-pixel annotations.

关键词： Convolutional neural networks(CNNs) scribble self-attention video object segmentation weakly supervised

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Improved A∗Algorithm based on Multi-Layers and Multi-Constraints 23

Improved A∗Algorithm based on Multi-Layers and Multi-Constr...

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4th International Conference on Artificial Intelligence in Electronics Engineering, AIEE 2023

作者： Han, Jian Zhou, Lili Tong, Jiahui Sun, Shiguo Hou, Mingyun Beijing Electro-Mechanical Engineering Institute China and Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9781450399517

In this study, an improved A∗algorithm based on multi-layers and multi-constraints is proposed for solving the problem that A∗algorithm must detour when encounters obstacles due to the deficiency of vertical dimension. Detailed obstacle classification and shift method among layers are introduced to make the mathematical environment closer to the real environment and support the calculation of proposed cost function. In the procedure of planning, more interested points are taken into consideration to increase the opportunity of find more reasonable path and achieve lower route cost during approaching the target. Shared forbidden area and shift cost mechanism are set to make sure the trend is right without shift too often. The improved algorithm can provide a better and flexible solution to cross obstacles other than make a detour, so the optimal route find by it has a shorter length than that by the traditional one. © 2023 ACM.

关键词： Cost functions

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Relative Localization for UAV-UGV Based on Correlation of Bearing and Distance 20

Relative Localization for UAV-UGV Based on Correlation of Be...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Guo, Jia Hu, Kang Liu, Jinting State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology No.5 Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

To ensure reliable localization for Unmanned Aerial Vehicles(UAVs) in the presence of uncertain speed of the Unmanned Ground Vehicle (UGV), this study examines the relative localization problem of UAV-UGV using distance and bearing measurements. A Correlation of Bearing and Distance-based Relative Localization (CBDRL) algorithm is proposed in this paper under this scenario. The estimation of altitude, distance, and angle are simplified into a representation of the relative positioning between the UAV and UGV. The relative height difference is measured using the barometer in the algorithm. To determine the relative distance, Time of Arrival (TOA) ranging and Ultra Wide Band (UWB) communication are utilized. The relative direction measurement is then determined using the correlations of bearing and distance. We integrate these observations with height, direction, and distance data in an Extended Kalman Filter(EKF) to provide accurate and reliable relative position estimates that allow the UAV to track the target. The simulation results indicate that the CBDRL method developed in this study is superior to previous relative localization algorithms that rely on multi-sensor fusion, and can significantly enhance the accuracy of UAV positioning provided that range and angle measurements are precise enough. © 2023 IEEE.

关键词： Antennas

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A Method for Marine Ship Formation Intention Recognition based on BiConvLSTM-Attention 3

A Method for Marine Ship Formation Intention Recognition bas...

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3rd International Conference on Electronic Information Engineering and Computer Science, EIECS 2023

作者： Xi, Yunqiao Zhang, Junping Liu, Jian Wang, Linlin Xu, Hongfeng Chen, Linxiu Jiang, Jixiang Harbin Institute of Technology School of Electronics and Information Engineering Harbin China Institute of Electrical and Mechanical Engineering Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350316674

To solve the problem that current dynamic intention recognition methods fail to make full use of time domain variation information between multi-temporal group targets, which leads to low accuracy of intention recognition. This paper proposes a bidirectional convolutional long short term memory-attention network for marine formation target intention recognition. The network takes the multi-source trajectory data of the marine ship formation target as the input, extracts and uses the target change rule and time domain characteristics of the Marine formation data, and trains the model to have the ability to independently learn the weight of information in different time periods. The simulation results show that the method has good performance and can meet the needs of practical application. © 2023 IEEE.

关键词： intention recognition long short-term marinship formation temporal features

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An Optimal Scheduling Strategy for Wind-PV and Multi-Type Energy Storage Co-Generation system 6

An Optimal Scheduling Strategy for Wind-PV and Multi-Type En...

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6th International Conference on Power and Energy Applications, ICPEA 2023

作者： Ma, Huan Tian, Hao Zhang, Kunpeng Liu, Yutian Shandong Electric Power Research Institute Jinan China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan China

ISBN: (纸本)9798350359053

Multi-type energy storage is essential for managing fluctuations in renewable energy power and increasing the consumption rate of renewable energy. In this paper, an optimal scheduling strategy for the co-generation system comprising wind power, photovoltaic power, electrical energy storage, and hydrogen energy storage is proposed. The strategy consists of a global optimization model and an application-oriented Pareto optimal solution screening methodology. The global optimization model establishes a multi-objective optimization model based on meteorological prediction information that considers the intended output power completion of the co-generation system, the remaining equivalent power of the energy storage plant, and the equivalent production of hydrogen. The NSGA-II is utilized to solve the global optimization model and obtains multiple Pareto optimal solutions. The optimal solutions are screened by applying the application-oriented Pareto optimal solution screening methodology. Finally, a co-generation plant in Shandong Province is presented to validate the effectiveness of the proposed approach in mitigating wind variability and encouraging the adoption of renewable energy sources. © 2023 IEEE.

关键词： Multiobjective optimization

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Meta-Learning Multi-Scale Radiology Medical Image Super-Resolution

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Computers, Materials & Continua 2023年第5期75卷 2671-2684页

作者： Liwei Deng Yuanzhi Zhang Xin Yang Sijuan Huang Jing Wang Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration School of AutomationHarbin University of Science and TechnologyHarbin150080HeilongjiangChina Department of Radiation Oncology Sun Yat-sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhou510060GuangdongChina Faculty of Rehabilitation Medicine Biofeedback LaboratoryGuangzhou Xinhua UniversityGuangzhou510520GuangdongChina

High-resolution medical images have important medical value,but are difficult to obtain *** by hardware equipment and patient’s physical condition,the resolution of directly acquired medical images is often not ***,many researchers have thought of using super-resolution algorithms for secondary processing to obtain high-resolution medical ***,current super-resolution algorithms only work on a single scale,and multiple networks need to be trained when super-resolution images of different scales are *** definitely raises the cost of acquiring high-resolution medical ***,we propose a multi-scale superresolution algorithm using *** algorithm combines a metalearning approach with an enhanced depth of residual super-resolution network to design a meta-upscale *** meta-upscale module utilizes the weight prediction property of meta-learning and is able to perform the super-resolution task of medical images at any ***,we design a non-integer mapping relation for super-resolution,which allows the network to be trained under non-integer magnification *** to the state-of-the-art single-image super-resolution algorithm on computed tomography images of the pelvic *** meta-learning multiscale superresolution algorithm obtained a surpassing of about 2%at a smaller model *** on different parts proves the high generalizability of our ***-scale super-resolution algorithms using meta-learning can compensate for hardware device defects and reduce secondary harm to patients while obtaining high-resolution medical *** can be of great use in imaging related fields.

关键词： Super resolution deep learning meta learning computed tomography

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Road Underground Target Detection in Ground Penetrating Radar Images Based on YOLO Models

Road Underground Target Detection in Ground Penetrating Rada...

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2023 China Automation Congress, CAC 2023

作者： Li, Ting Xue, Wei Yang, Xinya Wu, Dongchang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350303759

Ground penetrating radar (GPR) is extensively employed for subsurface road target detection, offering benefits such as convenience, nondestructive testing, rapid data acquisition, and superior resolution. Despite these advantages, interpreting GPR data often depends on the expertise of professionals, resulting in low detection efficiency and low accuracy. To address these challenges, this study introduces an intelligent detection technique for GPR images, utilizing an enhanced YOLOv5 framework. First, considering the problems of the small amount of GPR image datasets and the unclear characteristics caused by the complex underground media, a Dense-C3 module is built by utilizing the structure of DenseNet to enhance the network's capability for extracting features. Subsequently, a channel and spatial hybrid attention module is introduced into the backbone for feature refinement and improving the efficiency. Finally, the multi-class focal loss function is devised to enhance the precision in cases of imbalanced sample classes. Experimental results show that the proposed model surpasses the original YOLOv5 model and various contemporary advanced models. © 2023 IEEE.

关键词： Efficiency

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