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Trajectory control and Fair Communications for Multi-UAV Networks: A Federated Multi-Agent Deep Reinforcement Learning Approach

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IEEE Transactions on Wireless Communications 2025年

作者： Tarekegn, Getaneh Berie Tesfaw, Belayneh Abebe Juang, Rong-Terng Saha, Dola Tarekegn, Robel Berie Lin, Hsin-Piao Tai, Li-Chia Nycu Department of Electrical and Computer Engineering 1001 University Road Hsinchu300 Taiwan Nycu Institute of Electrical and Control Engineering 1001 University Road Hsinchu300 Taiwan National Taipei University of Technology Department of Electrical Engineering and Computer Science Taipei10608 Taiwan National Taipei University of Technology Institute of Aerospace and System Engineering Taipei10608 Taiwan University at Albany Suny Department of Electrical and Computer Engineering AlbanyNY12222 United States

Due to their highly flexible deployment and agility features, unmanned aerial vehicles (UAVs) serving as aerial base stations are increasingly being used in challenging environments, including emergency communication, traffic offloading, and failures of existing communications infrastructure. A reliable and effective communication service requires 3D deployment and autonomous UAV trajectory optimization in each time slot. While most prior approaches focus on trajectory design that maximizes communication coverage or network throughput without considering fairness as well as computation time. This paper presents a multi-UAV trajectory control and fair communication (TCFC) scheme that maximizes ground user data rate and communication coverage while ensuring service fairness in a UAV-aided wireless communications system. The proposed TCFC scheme employs a two-stage learning approach. Firstly, it develops a gated recurrent unit-based link quality estimation model to assess each user's link quality over time. Then, a federated multi-agent deep reinforcement learning (FedMADRL) algorithm is utilized to continuously adjust the trajectory of the UAVs, optimizing communication performance. We evaluated our proposed system using real channel measurement data, i.e., amplitude and phase signal information. The results show that the proposed TCFC scheme reduces computation time by 26.91% and provides comparable network performance with the baseline methods while improving DRL agents' privacy. © 2025 IEEE.

关键词： Deep reinforcement learning

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Influence of contact layer on the sulphur corrosion of copper conductors in power transformers

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High Voltage 2022年第1期7卷 176-184页

作者： Lijun Yang Dong Ding Yuan Yuan Sihang Gao Yuncai Lu State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing UniversityChongqingChina College of Material Science and Engineering Chongqing UniversityChongqingChina Key Laboratory of Industrial Internet of Things and Networked Control Ministry of EducationChongqing University of Posts and TelecommunicationsChongqingChina State Grid Jiangsu Electric Power Co. Ltd.Electric Power Research InstituteNanjingChina

Owing to the corrosive sulphides in the mineral insulating oil such as dibenzyl disul-phide(DBDS),copper windings in oil‐immersed transformers may suffer sulphur *** study investigates the influence of different contact conditions on the corrosion of copper conductors in ***‐immersed accelerated corrosion experiment was conducted on copper conductors with various contact materials and different layers of insulating *** surface micromorphology,deposition compo-nent and the potentiodynamic polarization characteristics of copper conductors were *** results show that copper with different contact materials suffer sulphur corrosion;conversely,bare copper rarely *** was also verified that the existence of a particular gap between copper and contact layer is a significant factor in sulphur corrosion by the formation of a concentration cell on the copper *** insu-lating paper wrapped around copper conductors does not increase the corrosion ten-dency of copper;however,it contributes to the formation of a region concentrated with DBDS,Cu^(2+),H^(+)by adsorption and impediment,which plays a key role in facilitating the sulphur corrosion of copper ***,sulphur corrosion can also occur on other metal parts in transformers when there is a particular gap on surfaces other than copper.

关键词： corrosion copper sulphur

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Can Digital Intelligence and Cyber-Physical-Social systems Achieve Global Food Security and Sustainability?

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IEEE/CAA Journal of Automatica Sinica 2023年第11期10卷 2070-2080页

作者： Yanfen Wang Mengzhen Kang Yali Liu Juanjuan Li Kai Xue Xiujuan Wang Jianqing Du Yonglin Tian Qinghua Ni Fei-Yue Wang College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049 Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408 State Key Laboratory of Tibetan Plateau Earth System Environment and ResourcesInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Grassland Science Beijing Forestry UniversityBeijing 100083China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China State Key Laboratory of Plateau Ecology and Agriculture Qinghai UniversityXining 810016 Key Laboratory of Adaptation and Evolution of Plateau Biota Northwest Institute of Plateau BiologyChinese Academy of SciencesXining 810001 Binzhou Institute of Technology Weiqiao-UCAS Science and Technology ParkBinzhou 256606China Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408China Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078 State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078 Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China IEEE

Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship. Agricultural production can be regarded as a form of carbon sequestration *** the perspective of the natural-social-economic complex ecosystem, excessive water usage in food production will aggravate regional water pressure for both domestic and industrial purposes. Hence, achieving a harmonious equilibrium between carbon and water resources during the food production process is a key scientific challenge for ensuring food security and sustainability. Digital intelligence(DI) and cyber-physical-social systems(CPSS) are emerging as the new research paradigms that are causing a substantial shift in the conventional thinking and methodologies across various scientific fields, including ecological science and sustainability studies. This paper outlines our recent efforts in using advanced technologies such as big data, artificial intelligence(AI), digital twins, metaverses, and parallel intelligence to model, analyze, and manage the intricate dynamics and equilibrium among plants, carbon, and water in arid and semiarid ecosystems. It introduces the concept of the carbon-water balance and explores its management at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Additionally, we elucidate the significance of agricultural foundation models as fundamental technologies within this context. A case analysis of water usage shows that, given the limited availability of water resources in the context of the carbon-water balance, regional collaboration and optimized allocation have the potential to enhance the utilization efficiency of water resources in the river basin. A suggested approach is to consider the river basin as a unified entity and coordinate the relationship between the

关键词： Carbon-water balance decision-support digital intelligence(DI) foundation models planning

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Significant Wave Height Prediction Based on VMD-SA-MLP-BP

Significant Wave Height Prediction Based on VMD-SA-MLP-BP

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2023 China Automation Congress, CAC 2023

作者： Wu, Yining Zhang, Runfeng Liu, Fang Liu, Zhenzhong Wu, Jianguo Dong, Haonan School of Mechanical Engineering Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education China Yichang Research Institute of Testing Technology Yichang443003 China Tianjin Hanhailanfan Marine Technology Co. Ltd. Tianjin300457 China School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9798350303759

Waves seriously impact port construction, worldwide route planning, military activities, and wave power generation. To improve the accuracy of significant wave height prediction, we proposed a novel prediction method, a multi-layer perceptron combined with a backpropagation adjustment (MLP-BP) prediction model that combines mutation mode decomposition (VMD) and a simulated annealing optimization algorithm (SA). Firstly, we use the variable modulus method to decompose the significant wave height sequence data and transform the wave height sequence into multiple different sub-modes (IMF) to reduce the complexity and non-stationarity of the data. Secondly, the simulated annealing algorithm (SA) is used to optimize the weight and bias of the MLP-BP neural network to find the optimal parameter configuration and improve the performance and generalization ability of the prediction model. Finally, the decomposed sub-modal components of each significant wave height sequence are inserted into the MLP-BP neural network and the predicted values of each element are summed to obtain the final significant wave height prediction. The prediction results of the SSA-MLP-BP, PSO-MLP-BP, SA-MLP-BP, and VMD-SA-MLP-BP were compared and demonstrated that the VMD-SA-MLP-BP model performed best. The MAE, MAPE, MSE, RMSE, and R2 of the prediction evaluation indexes were 0.036 m, 11.7%, 0.004 m2, 0.067 m, and 0.983, respectively, which performed well in predicting significant wave height. © 2023 IEEE.

关键词： Variational mode decomposition

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Improved Auction Algorithm for Weapon Target Assignment with Firepower-Health Model

Improved Auction Algorithm for Weapon Target Assignment with...

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Chinese control Conference (CCC)

作者： Shuobo Wang Yong Heng Yongzhao Hua Xiwang Dong Zhang Ren Institute of Artificial Intelligence Beihang University Beijing P.R. China Beijing Institute of Electronic System Engineering Beijing PR China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing P.R. China

This paper proposes an improved auction algorithm to optimize the efficiency of dynamic weapon target assignment (WTA) problem. Firstly, the dynamic battlefield environment of firepower-health model is analyzed and the constraints of weapon assignment problem are established. The firepower-health model is about the idea of adding constraints of weapon firepower and target health to promote the result of assignment more effectively. Secondly, in order to improve the computing speed of WTA algorithm, the penalty mechanism is introduced in the compensation auction algorithm. The main idea of improved algorithm is to reduce the extra consuming of the weapon during the assignment, from which penalty mechanism can optimize the assignment results and reduce the number of algorithm iterations by punishing the overkilled target under certain rules. Finally, the simulation results based on the dynamic firepower-health model show that the proposed algorithm can meet the requirements of firepower allocation, and can promote the effectiveness of assignment with high real-time response.

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Temperature and strain sensitivities of surface and hybrid acoustic wave Brillouin scattering in optical microfibers

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Chinese Physics B 2022年第9期31卷 333-339页

作者： Yi Liu Yuanqi Gu Yu Ning Pengfei Chen Yao Yao Yajun You Wenjun He Xiujian Chou Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control SystemMinistry of Education and Shanxi ProvinceTaiyuan 030024China Taiyuan University of Technology Institute of Optoelectronic EngineeringCollege of Physics and OptoelectronicsTaiyuan 030024China Strong Digital Technology Co. Ltd.(Thinvent)Nanchang 410000China North University of China Key Laboratory of Instrumentation Science and Dynamic Measurement Ministry of EducationTaiyuan 030051China North University of China College of Mechatronics EngineeringTaiyuan 030051China North University of China Science and Technology on Electronic Test and Measurement LaboratorySchool of Instrument and ElectronicsTaiyuan 030051China

Temperature and strain sensitivities of surface acoustic wave(SAW)and hybrid acoustic wave(HAW)Brillouin scat-tering(BS)in 1μm-1.3μm diameter optical microfibers are *** contrast to stimulated Brillouin scattering(SBS)from bulk acoustic wave in standard optical fiber,SAW and HAW BS,due to SAWs and HAWs induced by the coupling of longitudinal and shear waves and propagating along the surface and core of microfiber respectively,facilitate innovative detection in optical microfibers *** highest temperature and strain sensitivities of the hybrid acoustic modes(HAMs)are 1.082 MHz/℃and 0.0289 MHz/με,respectively,which is suitable for microfiber sensing applica-tion of high temperature and strain ***,the temperature and strain sensitivities of the SAMs are less affected by fiber diameter changes,ranging from 0.05 MHz/℃/μm to 0.25 MHz/℃/μm and 1×10^(-4) MHz/με/μm to 5×10^(-4) MHz/με/μm,*** can be found that that SAW BS for temperature and strain sensing would put less stress on manufacturing constraints for optical ***,the simultaneous sensing of temperature and strain can be realized by SAW and HAW BS,with temperature and strain errors as low as 0.30℃-0.34℃and 14.47με-16.25με.

关键词： Brllouin scatering surface acoustic waves hybrid acoustic waves optical microfiber sensing

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A Method for Reconstructing the Shape of Wing Panels Based on Fiber Optic Sensors and Tomographic Imaging Principles

A Method for Reconstructing the Shape of Wing Panels Based o...

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Prognostics and system Health Management Conference (PHM-Qingdao)

作者： Jun Zhan Jie Zeng Chao Xiang Jinpeng Cui Cheng Zeng Linfeng Zhu Mingyu Lu State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and Astronautics Nanjing China Aviation key laboratory of science and technology on aero electromechanical system integration Nanjing engineering institute of aircraft system jincheng AVIC Nanjing China Changping District Xiaotangshan Future Science and Technology City COMAC Beijing Aircraft Technology Research Institute Beijing China

ISBN: (数字)9798350354010

ISBN: (纸本)9798350354027

The aircraft wing structure shape reconstruction method based on discrete strain information not only provides data support for the digital collaborative health monitoring and prediction technology of wing structure but also helps to improve the aerodynamic shape and flight quality of the aircraft, achieve structural stealth, and enhance the pointing accuracy of the on-board conformal antenna. As result, a wing skin panel shape reconstruction method based on the principle of tomographic imaging and strain information perception is proposed. According to the idea of tomographic imaging, a “non-intrusive” layout form that only requires sensors to be arranged on the periphery of the monitoring area is designed, breaking through the limitation that sensors can not be arranged in the monitoring area under special working conditions. A method for constructing the deflection shape function of the wing skin panel based on the concept of synthetic curvature is proposed, solving the problem of error accumulation and elimination of deformation inversion at non-monitoring points of the measured structure caused by the uncertainty of the limited discrete layout of sensors and the choice of interpolation fitting method. On this basis, a model deformation monitoring and inversion system for wing skin panel based on fiber optic grating sensors is constructed. The experimental results show that under the single-end fixed bending and torsion working condition, the average relative error of the panel model shape reconstruction is 4.17%. Under the double-end fixed double-concentrated load working condition, the average relative error of the shape reconstruction is 8.07%. The wing deformation distribution information reconstructed by the method proposed in this paper can be mapped onto the virtual twin model of the wing, providing technical support for the safety assessment, early warning, and on-condition maintenance of the entire service life of key structures of the aircraft.

关键词： Employee welfare Shape Deformation Layout Imaging Sensors Aircraft Monitoring Image reconstruction Strain

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The Trajectory Re-Planning Method of the Hyper-Sonic Vehicle Facing Sudden Threats

The Trajectory Re-Planning Method of the Hyper-Sonic Vehicle...

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International Conference on control and Automation (ICCA)

作者： Jie Ren Jianglong Yu Xiwang Dong Zhang Ren School of Automation Science and Electrical Engineering Beihang University Beijing China Institute of Unmanned System Beihang University Beijing P.R. China Institute of Artificial Intelligence Beihang University Beijing P.R. China Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing P.R. China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

Aiming at the trajectory re-planning problem of multiple hyper-sonic vehicles with the time coordination under sudden threats, a time-coordinated fast trajectory re-planning method was proposed to avoid the no-fly zone. Firstly, the three-dimensional trajectory planning problem of the vehicle is decomposed into the longitudinal trajectory planning problem and the transverse trajectory planning problem. Secondly, a single sudden threat is regarded as a circular no-fly zone, and the circumvention of no-fly zone can only be considered in a transverse trajectory planning. Based on the in-depth study of the longitudinal trajectory planning with flight time constraints and range constraints, a reinforcement learning method is introduced into the transverse trajectory re-planning, and a fast tilting angle flipping self decision method based on the reinforcement learning is proposed. Finally, by training DQN to generate a tilting angle reversal decision maker, a fast three-dimensional trajectory re-planning method that can avoid the no-fly zone is realized. The proposed trajectory re-planning method not only has a fast trajectory re-planning speed, but also greatly improves the penetration probability against sudden threats. The simulation results show the feasibility and effectiveness of the proposed method.

关键词： Training Automation Trajectory planning Simulation Reinforcement learning Trajectory Planning

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Cooperative Task Reconstruction Allocation for Unmanned Swarm systems Based on MGGA and SAA

Cooperative Task Reconstruction Allocation for Unmanned Swar...

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International Conference on control and Automation (ICCA)

作者： Jintong Yu Yongzhao Hua Xiwang Dong Qingdong Li Zhang Ren Institute of Artificial Intelligence Beihang University Beijing P.R. China Institute of Unmanned System Beihang University Beijing P.R. China Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing P.R. China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

Multi-unmanned agent collaboration technology is a key aspect of operations. How to reasonably assign tasks to unmanned agents before operations to maximize the overall benefits is a long-standing problem for researchers. This study systematically addresses the above issues and establishes a multi-agent task reconstruction model based on the reconnaissance, strike and assessment task background. This model includes two types of task allocation algorithms. One is task pre-allocation, which is a static task allocation before task execution. A Multi-Gene Genetic Algorithm (MGGA)is proposed for this purpose. The other is Sequential Auction Algorithm(SAA), which deals with the reallocation of tasks in response to unexpected situations during task execution. Experimental results show that, compared with other algorithms, MGGA can get the lowest fitness value under various experimental conditions. Meanwhile, SAA can handle task reallocation problems caused by various dynamic events.

关键词： Heuristic algorithms Sociology system recovery Reconstruction algorithms Reconnaissance Resource management Time factors

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An overview for monitoring and prediction of pathogenic microorganisms in the atmosphere

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Fundamental Research 2024年第3期4卷 430-441页

作者： Jianping Huang Danfeng Wang Yongguan Zhu Zifeng Yang Maosheng Yao Xiaoming Shi Taicheng An Qiang Zhang Cunrui Huang Xinhui Bi Jiang Li Zifa Wang Yongqin Liu Guibing Zhu Siyu Chen Jian Hang Xinghua Qiu Weiwei Deng Huaiyu Tian Tengfei Zhang Tianmu Chen Sijin Liu Xinbo Lian Bin Chen Beidou Zhang Yingjie Zhao Rui Wang Han Li Collaborative Innovation Center for Western Ecological Safety College of Atmospheric SciencesLanzhou UniversityLanzhou 730000China Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China National Clinical Research Center for Respiratory Disease Guangzhou Institute of Respiratory HealthFirst Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease(Guangzhou Medical University)Guangzhou 510230China College of Environmental Sciences and Engineering Peking UniversityBeijing 100871China China CDC Key Laboratory of Environment and Population Health National Institute of Environmental HealthChinese Center for Disease Control and PreventionBeijing 100021China Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health School of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China Vanke School of Public Health Tsinghua UniversityBeijing 100084China State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization Guangzhou Institute of GeochemistryChinese Academy of SciencesGuangzhou 510640China National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Center for Pan-third Pole Environment Lanzhou UniversityLanzhou 730000China College of Atmospheric Sciences Lanzhou UniversityLanzhou 730000China School of Atmospheric Sciences Sun Yat-sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 510640

Corona virus disease 2019(COVID-19)has exerted a profound adverse impact on human *** have demonstrated that aerosol transmission is one of the major transmission routes of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Pathogenic microorganisms such as SARS-CoV-2 can survive in the air and cause widespread infection among *** monitoring of pathogenic microorganism transmission in the atmosphere and accurate epidemic prediction are the frontier guarantee for preventing large-scale epidemic *** of pathogenic microorganisms in the air,especially in densely populated areas,may raise the possibility to detect viruses before people are widely infected and contain the epidemic at an earlier *** multi-scale coupled accurate epidemic prediction system can provide support for governments to analyze the epidemic situation,allocate health resources,and formulate epidemic response *** review first elaborates on the effects of the atmospheric environment on pathogenic microorganism transmission,which lays a theoretical foundation for the monitoring and prediction of epidemic ***,the monitoring technique development and the necessity of monitoring pathogenic microorganisms in the atmosphere are summarized and ***,this review introduces the major epidemic prediction methods and highlights the significance to realize a multi-scale coupled epidemic prediction system by strengthening the multidisciplinary cooperation of epidemiology,atmospheric sciences,environmental sciences,sociology,demography,*** summarizing the achievements and challenges in monitoring and prediction of pathogenic microorganism transmission in the atmosphere,this review proposes suggestions for epidemic response,namely,the establishment of an integrated monitoring and prediction platform for pathogenic microorganism transmission in the atmosphere.

关键词： Aerosol transmission Epidemic monitoring methods Epidemic prediction modelsEpidemic response Multidisciplinary cooperation

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