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63rd IEEE Conference on Decision and control, CDC 2024

作者： Kurtoglu, Deniz Yucelen, Tansel Tran, Dzung Casbeer, David Garcia, Eloy University of South Florida Laboratory for Autonomy Control Information and Systems Department of Mechanical Engineering TampaFL33620 United States Air Force Research Laboratory Control Science Center Wright-Patterson Air Force Base OH45433 United States

ISBN: (纸本)9798350316339

Many multiagent system applications necessitate each agent to separately visit a specific location in space at a particular moment in time (i.e., spatiotemporal points). To this end, we propose a finite-time distributed control protocol over directed acyclic graphs that addresses the problem of multiagent placement at spatiotemporal points. In particular, we demonstrate that the proposed protocol can drive the trajectories of agents to their spatiotemporal points at different user-defined times by employing methods ranging from time transformation to input-to-state stability and Lyapunov stability. To show the efficacy of the proposed protocol, we also give two illustrative numerical examples. © 2024 IEEE.

关键词： Directed graphs

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Chemical bond parameters and microwave dielectric properties of CaLaAl3O7 ceramics with layer structure

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Ceramics International 2025年第15期51卷 20798-20804页

作者： Yang, Hongcheng Huang, Xier Zheng, Yixuan Zhang, Jin Li, Enzhu School of New Energy and Materials Southwest Petroleum University Chengdu610500 China National Engineering Research Center of Electromagnetic Radiation Control Materials and Key Laboratory of Multi-Spectral Absorbing Materials and Structures of Ministry of Education University of Electronic Science and Technology of China Chengdu610054 China

Sintered at 1575 °C, the single phase CaLaAl3O7 ceramics were obtained and investigated on the sensitivity of chemical bond to the stability of layer structure. LaAlO3 and CaAl2O4 are the secondary phases in the sintering temperature range of 1350∼1550 °C, contributing to the variation of relative density, dielectric constant and quality factors. As a candidate of microwave dielectric ceramics of aluminate, pure CaLaAl3O7 possesses the microwave dielectric properties of ɛr = 6.26, Q × f = 22750 GHz, τf = −39.8 ppm/°C. Based on the calculation of chemical bond traits and cation polarization, modification of Ca/La site may have primary influence on ɛr. Al(1)-O and Al(2)-O bonds make mainly contribution on lattice energy and bond energy, indicating [AlO4] frame paly crucial role on crystal structure stability. It is prior to design substitution for Al to adjust the layer structure and optimize the dielectric loss for CaLaAl3O7 ceramics. The systematical results of this study establish that determination of contributions of chemical bond to structure stability is a key dial for tuning crystal structure and properties in ternary aluminate solids. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Aluminum oxide

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A Probabilistic Topology Inference Method for Networked Dynamical System via Single Excitation 63

A Probabilistic Topology Inference Method for Networked Dyna...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Jiao, Qing Li, Yushan He, Jianping Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Dept. of Automation Shanghai China

ISBN: (纸本)9798350316339

A growing number of works have investigated inferring the topology of networked dynamical systems from observations, such as to better understand the system behaviour. Despite the tremendous advances, most of them require the observations to be abundant. This paper focuses on inferring the topology by injecting single excitation on a node and collecting several steps of noisy observations. The problem is challenging because the noises cannot be depressed in several observations and are mixed with the injected excitation, making it hard to directly reveal the topology. To practice, we develop a probabilistic method based on the hypothesis test framework. First, we infer the neighbors that are within h-hop of the excited node and derive the accuracy guarantees. Then, we extend the method to infer the exact h-hop neighbors. A computable lower bound for the accuracy probability is established to provide confidence support in the inference procedures. Furthermore, we give the conditions of excitation input to ensure a desired inference probability, which provides guidance for the input design. Numerical simulations are conducted to verify the effectiveness of the proposed method. © 2024 IEEE.

关键词： Network topology

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A new ChatGPT-empowered,easy-to-use machine learning paradigm for environmental science

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Eco-Environment & Health 2024年第2期3卷 131-136页

作者： Haoyuan An Xiangyu Li Yuming Huang Weichao Wang Yuehan Wu Lin Liu Weibo Ling Wei Li Hanzhu Zhao Dawei Lu Qian Liu Guibin Jiang State Key Laboratory of Environmental Chemistry and Toxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China Biomedical Engineering Institute School of Control Science and EngineeringShandong UniversityJinan 250061China

The quantity and complexity of environmental data show exponential growth in recent ***-quality big data analysis is critical for performing a sophisticated characterization of the complex network of environmental *** learning(ML)has been employed as a powerful tool for decoupling the complexities of environmental big data based on its remarkable fitting ***,due to the knowledge gap across different subjects,ML concepts and algorithms have not been well-popularized among researchers in environmental *** this context,we introduce a new research paradigm—“ChatGPT t ML t Environment”,providing an unprecedented chance for environmental researchers to reduce the difficulty of using ML *** instance,each step involved in applying ML models to environmental sustainability,including data preparation,model selection and construction,model training and evaluation,and hyper-parameter optimization,can be easily performed with guidance from *** also discuss the challenges and limitations of using this research paradigm in the field of environmental ***,we highlight the importance of“secondary training”for future application of“ChatGPT t ML t Environment”.

关键词： Machine learning Environmental application ChatGPT Secondary training

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Skewed Pins Detection of Aviation Connectors Based on Multi-Modal Cooperative Perception

Skewed Pins Detection of Aviation Connectors Based on Multi-...

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2024 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2024

作者： Li, Jiaming Ren, Cheng Xu, Jiaxin Wang, Yao Xu, Hanlin Guan, Xinping Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China

ISBN: (纸本)9798331507886

Aviation electrical connectors are critically important components in electrical wiring interconnection systems. Currently, connector defect detection relies entirely on manual inspection, which is error-prone and time-consuming. Due to the unique structural characteristics of aviation connectors, single-modality sensors often struggle to simultaneously detect both pins and holes. To address this issue, we propose a 3D skewed pins detection (3D-SPD) algorithm that integrates both 2D and 3D modals features. Due to the low quality of the raw connector data, we propose a connector point cloud enhancement (CPCE) algorithm that combines multi-view point clouds for point cloud fusion enhancement. Based on enhanced data, we perform skewed pin detection. Experimental results indicate that CPCE and 3D-SPD are effective in detecting skewed pins, achieving an accuracy rate exceeding 99%. Our algorithm can be deployed as an AI assistant on the edge device for the skewed pin detection. © 2024 IEEE.

关键词： defect detection machine vision multi-modal cooperative perception skewed pin

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A Enhanced Feature Extraction for 3D Object Detection 25

A Enhanced Feature Extraction for 3D Object Detection

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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Meng, Qingao Tong, Jigang Yang, Sen Xie, Tian Jin, Xin Tianjin University of Technology The School of Electrical Engineering and Automation Tianjin China Avic Xi'an Flight Automatic Control Research Institute National Key Laboratory of Science and Technology on Aircraft Control Xi'an China

ISBN: (纸本)9798350366600

3D object detection is crucial for autopilot and augmented reality applications. However, accurate feature extraction is the key to achieve high-precision detection, but traditional methods face the challenges of information loss and computational inefficiency. To address this, we propose an enhanced feature extraction method. We first divide the 3D space into voxel grids of varying scales. Then, using 3D sparse convolution, we extract features which are compressed along the Z axis to form BEV (Bird's Eye View) feature images. An efficient multi-scale attention mechanism is then employed to enhance these BEV features. The refined feature map is subsequently located and classified through a CT-stacking module and RPN (Region Proposal Network). Voxel features from the proposal and 3D backbone are passed through a voxel RoI pool to directly extract RoI features from the 3D features for further refinement. Finally, a cascaded attention network refines the proposal and strengthens confidence prediction. Experiments on test set validate our method effectiveness, showing improved accuracy over traditional voxel methods. Overall, this enhanced feature extraction technique offers a promising solution for 3D target detection, particularly in scenarios demanding high real-time performance and precision. © 2024 IEEE.

关键词： Feature extraction

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An Approach to Formation control of UAVs Based on Applying Adapted Kohonen Neural Network

An Approach to Formation Control of UAVs Based on Applying A...

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2023 IEEE Ural-Siberian Conference on Biomedical engineering, Radioelectronics and Information Technology, USBEREIT 2023

作者： Khachumov, Mikhail Ailamazyan Program Systems Institute of Ras Intelligent Control Laboratory Pereslavl-Zalessky Russia Federal Research Center' Computer Science and Control' of Ras Moscow Russia

ISBN: (纸本)9798350336054

The paper gives a statement and considers the solution of an urgent scientific problem of formation control for a group of unmanned aerial vehicles (UAVs) operating in an unstable environment. To construct the reference trajectories and allocate UAVs to positions of a given structure, an original approach is proposed based on the adapted Kohonen neural network with a set of metrics, including Euclidean, Mahalanobis and Euclidean-Mahalanobis distances. To implement the movement of a UAV group in a complex environment, we apply the principles of intelligent-geometric control, which allows to combine flexible intelligent and precise geometric control methods within one concept. When moving along a given route, UAVs use a set of allowable control strategies. The developed modeling scheme is designed to take into account wind loads and possibly dangerous rapprochement of vehicles. To reflect the dynamics of UAVs, a special module is used that contains transfer functions integrated into a single stabilization system with an autopilot. The proposed approach has shown promise when simulating a series of formation control problems. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Where to Turn: Road Fork Detection in Sparse 3D Point Cloud 3rd

Where to Turn: Road Fork Detection in Sparse 3D Point Clou...

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3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Hu, Di Zhang, Kai Zhong, Yipan Xu, Jiachen Yuan, Xia Zhao, Chunxia School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Research Institute of Intelligence Southwest Research Institute of Information Control Chengdu611700 China

ISBN: (纸本)9789819711024

Intersection detection plays a crucial role in localizing and planning the path of autonomous vehicles in urban environments. This paper presents a novel approach, PVWO, for adaptive intersection detection in autonomous vehicles equipped with 3D LiDAR. Firstly, the algorithm removes ground and obstacles effectively, and eliminates noise points. Secondly, a polyarticular viewpoints beam model is applied to detect the type and location of intersections. Thirdly, a linear feature extraction approach in a rolling window is proposed to detect road width and optimize key parameters, enhancing model robustness across different scenes. Compared to parallel intersection detection algorithms, our method exhibits excellent performance under diverse road conditions. Experiments in sparse point clouds show an average precision exceeding 89% and an average processing time of approximately 88 ms/frame. These results demonstrate that our method can accurately detect intersections in real-time, across various road structures. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Extraction

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Diminishing ether-oxygen content of electrolytes enables temperature-immune lithium metal batteries

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science China Chemistry 2023年第9期66卷 2700-2710页

作者： Tao Liu Jingnan Feng Zhe Shi Huajun Li Weina Zhao Minglei Mao Xiangzhen Zhu Yong-Sheng Hu Hong Li Xuejie Huang Liquan Chen Liumin Suo Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsChinese Academy of SciencesBeijing 100190China Qingdao Industrial Energy Storage Research Institute Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of SciencesQingdao 266101China Department of Nuclear Science and Engineering and Department of Materials Science and Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control Guangdong Key Laboratory of Environmental Catalysis and Health Risk ControlSchool of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China

The reversibility of lithium(Li) metal anodes is highly susceptible to temperature,owing to the aggravated side reactions at high temperatures and serious Li dendrite growth at low *** it is extremely challenging to simultaneously realize the high Li reversibility in both low and high temperature ***,an oxygen-free solvent(n-hexane,HEX) assisted with the hexyl methyl ether and 1 mol L^(-1)lithium bis(fluorosulfonyl)imide is proposed to constitute an electrolyte for temperatureimmune lithium metal *** demonstrates that the HEX not only greatly suppresses the solvent reduction even at high temperatures but also weaken the Li~+-solvent interaction for the facile Li-ion desolvation,leading to high Li Coulombic efficiencies(99.59% at 25℃,99.30%at 60℃ and 98.75% at -30℃) and the dendrite-free Li plating from -30℃ to 60℃.Benefitting from the low density and temperature-immune properties of our electrolyte,the sulfurized polyacrylonitrile(3.8mAh cm^(-2))||Li(60 μm) pouch-cells deliver 278 Wh kg^(-1)energy density and maintain the stable performance over 50 cycles,and retain 248 and 320 Wh kg^(-1) energy density at -30℃ and 60℃,*** work provides a new perspective on the electrolyte design for wide-temperature Li metal batteries.

关键词： wide temperature range oxygen-free solvent dendrite-free Li plating high Coulombic efficiencies lithium metal batteries

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Machine learning-driven optimization of plasma-catalytic dry reforming of methane

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Journal of Energy Chemistry 2024年第9期96卷 153-163页

作者： Yuxiang Cai Danhua Mei Yanzhen Chen Annemie Bogaerts Xin Tu Department of Electrical Engineering and Electronics University of LiverpoolLiverpool L693GJUK Research Group PLASMANT Department of ChemistryUniversity of AntwerpUniversiteitsplein 1BE-2610 Wilrijk-AntwerpBelgium College of Electrical Engineering and Control Science Nanjing Tech UniversityNanjing 211816JiangsuChina

This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)catalysts in a dielectric barrier discharge(DBD)non-thermal plasma reactor.A novel hybrid machine learning(ML)model is developed to optimize the plasma-catalytic DRM reaction with limited experimental *** address the non-linear and complex nature of the plasma-catalytic DRM process,the hybrid ML model integrates three well-established algorithms:regression trees,support vector regression,and artificial neural networks.A genetic algorithm(GA)is then used to optimize the hyperparameters of each algorithm within the hybrid ML *** ML model achieved excellent agreement with the experimental data,demonstrating its efficacy in accurately predicting and optimizing the DRM *** model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM *** found that the optimal discharge power(20 W),CO_(2)/CH_(4)molar ratio(1.5),and Ni loading(7.8 wt%)resulted in the maximum energy yield at a total flow rate of∼51 mL/***,we investigated the relative significance of each operating parameter on the performance of the plasma-catalytic DRM *** results show that the total flow rate had the greatest influence on the conversion,with a significance exceeding 35%for each output,while the Ni loading had the least impact on the overall reaction *** hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets,enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.

关键词： Plasma catalysis Machine learning Process optimization Dry reforming of methane Syngas production

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