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2023 China automation Congress, CAC 2023

作者： Chen, Kang Du, Shaochong Huo, Hong Fang, Tao Shanghai Jiao Tong University Department of Automation Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Shanghai Engineering Research Centre of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350303759

The earth observation satellite scheduling has always been critical for the maximum use of limited satellite resources, which basically includes scheduling ground target observation and observation data downloading. Due to the complexity of the mathematical model and its NP-hardness, current research usually splits it into two problems to simplify the model. In this paper, we propose a model of the integrated scheduling problem of satellite observation and data downloading (ISP-SODD) based on the decentralized partially observable Markov decision process (Dec-POMDP), treating each satellite as an agent with autonomous decision-making capability. A multi-agent deep reinforcement learning-based (MADRL-based) algorithm is proposed to solve it. A series of simulation experiments of different scales validate the effectiveness of the method and its advantages compared with the traditional heuristic algorithms. To the best of our knowledge, this study is the first attempt to apply multi-agent reinforcement learning to a multi-satellite scheduling scenario with downloading considerations. © 2023 IEEE.

关键词： Reinforcement learning

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Correction of Time-varying PMU Phase Angle Deviation with Unknown Transmission Line Parameters

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CSEE Journal of Power and Energy systems 2023年第1期9卷 315-325页

作者： Ancheng Xue He Kong Feiyang Xu Junbo Zhao Naichao Chang Joe H.Chow Haiyan Hong State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China Department of Electrical and Computer Engineering University of ConnecticutStorrs06268USA National Electric Power Dispatching and Control Center Beijing 100031China Department of Electrical Computerand Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNY 12180USA

Phasor measurement units(PMUs)provide useful data for real-time monitoring of the smart ***,there may be time-varying deviation in phase angle differences(PADs)between both ends of the transmission line(TL),which may deteriorate application performance based on *** address that,this paper proposes two robust methods of correcting time-varying PAD deviation with unknown parameters of TL(ParTL).First,the phenomena of time-varying PAD deviation observed from field PMU data are *** general formulations for PAD estimation are then *** simplify the formulations,estimation of PADs is converted into the optimal problem with a single ParTL as the variable,yielding a linear estimation of *** latter is used by second-order Taylor series expansion to estimate PADs *** reduce the impact of possible abnormal amplitude data in field data,the IGG(institute of Geodesy&Geophysics,Chinese Academy of Sciences)weighting function is *** using both simulated and field data verify the effectiveness and robustness of the proposed methods.

关键词： Correction line parameters parameter identification phasor measurement time-varying phase angle difference deviation

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The Neural Network Algorithm for Decision Support During control of the Welding Process by Robotic Complexes 15

The Neural Network Algorithm for Decision Support During Con...

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15th International Conference Management of Large-Scale system Development, MLSD 2022

作者： Fominykh, Dmitry Fuchedzhi, Nikolai Kushnikov, Oleg Laboratory of System Problems of Control and Automation in Mechanical Engineering Institute for Precision Mechanics and Control Problems of Ras Saratov Russia V.A. Trapeznikov Institute of Control Sciences of Ras Moscow Russia

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

The article proposes an algorithm for solving the problem of controlling the welding process in robotic technological complexes according to the quality criterion of the products. The statement of the problem is given and the model of system dynamics by J. Forrester is considered. Welding quality indicators in robotic complexes were used as system levels. Functional dependencies are taken by using the mathematical apparatus of artificial neural networks, in particular, radial basis functions that allow for rigid interpolation. The introduction of the models and algorithms discussed in the article will improve the quality of products using robotic technological complexes. © 2022 IEEE.

关键词： Robotics

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Learning Knowledge Evolution with Time Duration from Finer-Time-Granularity Temporal Knowledge Graph

Learning Knowledge Evolution with Time Duration from Finer-T...

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2023 China automation Congress, CAC 2023

作者： Du, Shaochong Chen, Kang Yang, Shijie Huo, Hong Fang, Tao Shanghai Jiao Tong University Department of Automation Shanghai China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai China Shanghai Engineering Research Centre of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350303759

How to represent the temporal information corresponding to each fact in temporal knowledge graphs (TKGs) effectively is always challenging. Most existing representation learning methods usually map the timelines of knowledges into multiple points and ignore the underlying continuous time property and periodic characteristics behind those dense timestamps in finer-time granularity temporal knowledge graphs. A novel Knowledge Evolution with Time Duration (KETD) model is proposed for knowledge representation of temporal knowledge graphs with finer-time granularities. It represents the entity embedding as a time-varying nonlinear function to find the specific continuous time property from dense timestamps. To the best of our knowledge, it is the first attempt to learn embeddings of time durations and combines them into embeddings of entities and relations to predict potential periodic facts. It also uses the temporal point process to capture the impact of historical facts on the current fact. The experiments on self-built finer-time granularity TKG of Satellite-to-Earth Communication (STEC) and two public datasets have demonstrated the superiority of KETD compared to some baseline approaches. © 2023 IEEE.

关键词： Knowledge graph

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Multi-Channel Based on Attention Network for Infrared Small Target Detection

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 414-427页

作者：张彦军王碧云蔡云泽 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Institute of Aerospace Control Technology Shanghai 201109China Infrared Detection Technology R&D Center of China Aerospace Science and Technology Corporation Shanghai 201109China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghai 200240China

Infrared detection technology has the advantages of all-weather detection and good concealment,which is widely used in long-distance target detection and tracking ***,the complex background,the strong noise,and the characteristics of small scale and weak intensity of targets bring great difficulties to the detection of infrared small targets.A multi-channel based on attention network is proposed in this paper,aimed at the problem of high missed detection rate and false alarm rate of traditional algorithms and the problem of large model,high complexity and poor detection performance of deep learning ***,given the difficulty in extracting the features of infrared multiscale and small dim targets,the multiple channels are designed based on dilated convolution to capture multiscale target ***,the coordinate attention block is incorporated in each channel to suppress background clutters adaptively and enhance target *** addition,the fusion of shallow detail features and deep abstract semantic features is realized by synthesizing the contextual attention fusion ***,it is verified that,compared with other state-of-the-art methods based on the datasets SIRST and MDFA,the proposed algorithm further improves the detection effect,and the model size and computational complexity are smaller.

关键词： infrared image small target detection deep learning attention mechanism feature fusion

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Data-Driven control of Distributed Event-Triggered Network systems

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 351-364页

作者： Xin Wang Jian Sun Gang Wang Frank Allgower Jie Chen the National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081 the Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China IEEE the Institute for Systems Theory and Automatic Control University of StuttgartStuttgart 70550Germany the Department of Control Science and Engineering Tongji UniversityShanghai 201804 the National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China

The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems(*** systems).To this end,we start by putting forth a novel distributed event-triggering transmission strategy based on periodic sampling,under which a model-based stability criterion for the closed-loop network system is derived,by leveraging a discrete-time looped-functional *** the model-based criterion with a data-driven system representation recently developed in the literature,a purely data-driven stability criterion expressed in the form of linear matrix inequalities(LMIs)is ***,the data-driven stability criterion suggests a means for co-designing the event-triggering coefficient matrix and the feedback control gain matrix using only some offline collected state-input ***,numerical results corroborate the efficacy of the proposed distributed data-driven event-triggered network system(ETS)in cutting off data transmissions and the co-design procedure.

关键词： Data-driven control distributed event-triggered network system(ETS) linear matrix inequalitie(LMI) looped-functional stability

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system Structure for Railway Switch Points and Signals Electrical Interlocking Powered by Renewable Energy Sources and Emergency Cable Network

System Structure for Railway Switch Points and Signals Elect...

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2024 International Conference on Industrial engineering, Applications and Manufacturing, ICIEAM 2024

作者： Efanov, Dmitrii V. Ruziev, Davron Kh. Khóroshev, Valerii V. Transport Higher School Of Mechanical Engineering Material And Transport Institute In Peter The Great St. Petersburg Polytechnic University St. Petersburg Russia Tashkent State Transport University 'Automation And Remote Control' Department Tashkent Uzbekistan Russian University Of Transport 'Automation Remote Control And Communication On Railway Transport' Department Moscow Russia 'Automation Remote Control And Communication On Railway Transport' Department Moscow Russia

ISBN: (纸本)9798350395013

Article propose a hybrid technology of power supply in the electrical interlocking systems development for railway stations. The main feed input is proposed to be carried out from renewable energy sources. Such sources are near the railway track. Redundant power supply should be provided using traditional cable networks with local placement. The article presents the structures of electrical interlocking systems based on hybrid technology. In addition, when supplying power to railway automation and remote control, the power supply must be guaranteed. That is why, at this stage of the transition, it is necessary to maintain redundant cable glands. In the future, a complete transition to energy supply from renewable energy sources is proposed. The authors considered the use of energy sources with solar panels. The following solutions are proposed for organizing the power supply of railway automation and remote-control devices: providing power supply in the yard neck with local power sources - solar panels, linking between wayside device and the signal box using fiber optic cables and radio channels. The main attention is paid to the environmentally friendly energy sources, the wire routing shorts and maintenance. © 2024 IEEE.

关键词： Energy efficiency

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High-precision flexible sweat self-collection sensor for mental stress evaluation

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npj Flexible Electronics 2024年第1期8卷 417-426页

作者： Chenhao Wang Zhengyu Wang Wei Wei Zhenjie Zhang Anne Ailina Li Guanghao Huang Xian Li Shuzhi Sam Ge Lianqun Zhou Hui Kong Institute for Future School of AutomationShandong Key Laboratory of Industrial Control TechnologyQingdao UniversityQingdao266071China ETH Zürich Department of Biosystems Science and EngineeringBio Engineering LaboratoryBasel4056Switzerland The University of Sydney 2006 SydneyAustralia Natl Univ Singapore Dept Elect&Comp EngnSingapore117576Singapore Suzhou Institute of Biomedical Engineering and Technology Chinese.Academy of SciencesSuzhou215163China

As a stress hormone existing in the human body,cortisol can reflect the psychological stress and health status in daily life,and is a potential biomarker of the body’s stress *** effectively collect sweat and accurately identify the target,this paper reports a flexible wearable cortisol detection device with outstanding reliability and *** imprinted polymer(MIP)ensures cortisol *** carbon nanotubes(CNT)on electrodes increase sensitivity,expanding the detection range to 10^(−3) to 10^(4) nM,with sensitivity at 189.2 nA/lg(nM).In addition,porous chitosan hydrogel(PCSH)collects sweat effectively,its adhesive properties and 80%swelling rate offer a low-cost alternative to *** printed circuit board(FPCB)and serpentine electrode(SE)ensure device *** non-invasive,highly sensitive device offers a novel method for mental stress monitoring and clinical diagnosis,advancing human physiological state monitoring.

关键词： stress durability swelling

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The Algorithm of Searching for Critical Combinations of Events During the Welding Process in Robotic Technological Complexes 15

The Algorithm of Searching for Critical Combinations of Even...

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15th International Conference Management of Large-Scale system Development, MLSD 2022

作者： Fominykh, Dmitry Baryshnikova, Elena Antipin, Sergei Institute for Precision Mechanics and Control Problems of Ras Laboratory of System Problems of Control and Automation in Mechanical Engineering Saratov Russia V.A. Trapeznikov Institute of Control Sciences of Ras Moscow Russia

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

The models and the algorithms for control the welding process in robotic complexes are considered under conditions of occurrence risk of critical combinations of events leading to emergency situations. Using the apparatus of dynamic graphs, the previously developed approach was modified by synthesizing and further analyzing new edges of the activities graph © 2022 IEEE.

关键词： Robotics

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Research on workflow recognition for liver rupture repair surgery

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Mathematical Biosciences and engineering 2024年第2期21卷 1844-1856页

作者： Men, Yutao Zhao, Zixian Chen, Wei Wu, Hang Zhang, Guang Luo, Feng Yu, Ming Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Medical Support Technology Research Department Systems Engineering Institute Academy of Military Sciences People’s Liberation Army Tianjin300161 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

Liver rupture repair surgery serves as one tool to treat liver rupture, especially beneficial for cases of mild liver rupture hemorrhage. Liver rupture can catalyze critical conditions such as hemorrhage and shock. Surgical workflow recognition in liver rupture repair surgery videos presents a significant task aimed at reducing surgical mistakes and enhancing the quality of surgeries conducted by surgeons. A liver rupture repair simulation surgical dataset is proposed in this paper which consists of 45 videos collaboratively completed by nine surgeons. Furthermore, an end-to-end SA-RLNet, a self attention-based recurrent convolutional neural network, is introduced in this paper. The self-attention mechanism is used to automatically identify the importance of input features in various instances and associate the relationships between input features. The accuracy of the surgical phase classification of the SA-RLNet approach is 90.6%. The present study demonstrates that the SA-RLNet approach shows strong generalization capabilities on the dataset. SA-RLNet has proved to be advantageous in capturing subtle variations between surgical phases. The application of surgical workflow recognition has promising feasibility in liver rupture repair surgery. ©2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons.

关键词： Image classification

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