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Parallel Factories for Smart Industrial Operations:From Big AI Models to Field Foundational Models and Scenarios Engineering

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IEEE/CAA Journal of Automatica Sinica 2022年第12期9卷 2079-2086页

作者： Jingwei Lu Xingxia Wang Xiang Cheng Jing Yang Oliver Kwan Xiao Wang Qingdao Academy of Intelligent Industries Qingdao 266114 The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190 Motion G Inc.Singapore 068898Singapore IEEE School of Artificial Intelligence Anhui UniversityHefei 230031

The rapid advancement of fundamental theories and computing capacity has brought artificial intelligence,internet of things, extended reality, and many other new intelligent technologies into our daily lives. Due to the lack of interpretability and reliability guarantees, it is extremely challenging to apply these technologies directly to real-world industrial systems. Here we present a new paradigm for establishing parallel factories in metaverses to accelerate the deployment of intelligent technologies in real-world industrial systems: QAII-1.0. Based on cyber-physical-social systems,QAII-1.0 incorporates complex social and human factors into the design and analysis of industrial operations and is capable of handling industrial operations involving complex social and human behaviors. In QAII-1.0, a field foundational model called Eu Artisan combined with scenarios engineering is developed to improve the intelligence of industrial systems while ensuring industrial interpretability and reliability. Finally, parallel oil fields in metaverses are established to demonstrate the operating procedure of QAII-1.0.

关键词： Cyber-physical-social system(CPSS) Industry5.0 Metaverses Parallel factories Parallel intelligence

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PFedSim: An Efficient Federated control Method for Clustered Training

IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION

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IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION 2022年 6卷 779-782页

作者： Chen, Yizhu Wang, Xiao Tian, Yonglin Wang, Fei Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Parallel Intelligence Res Ctr Qingdao 266000 Peoples R China

To further promote the implementation and application of artificial intelligence technology under data silos, federated ecology has defined a set of standardized and systematic solutions from upstream data to downstream applications from a systematic perspective. As the core of the federated ecology, federated control can transform the abstract tasks of federated management into concrete execution rules. Clustered training is a common cooperation rule for the personalized federated training task of multi-party cooperation. However, it is difficult to generalize in large-scale cooperation scenarios because of increased data transmission pressure and server storage burden. Therefore, this paper designs a personalized federated control method based on similarity measures(pFedSim) so that the server can accurately distribute the cluster model to clients, thereby reducing the transmission cost. Compared with the existing clustered training method IFCA, pFedSim transfers the selection rights of cluster models from the client to the server. Model selection preference, accurate distribution of cluster models. Experiments show that in the personalized training task with s clusters, the method can obtain the same model level with 1/s data transmission. It is better than the current optimal clustering training method Macro-Acc increased by 2.25%.

关键词： Federated control personalized federated training clustered training

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System Dynamics-Based Analysis on Factors Influencing Artificial Intelligence Talents Training

IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION

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IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION 2022年 6卷 753-757页

作者： Jing, Sifeng Liu, Xiwei Gong, Xiaoyan Zhao, Hongxia Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Inst Smart Educ Syst Qingdao 266044 Peoples R China

There are gaps between education supply and industrial demand of talents in intelligent era. Thus, the shortage of artificial intelligence(AI) talents becomes the top challenges facing China's companies. Hence it is essential to implement educational reform to improve quality of education supply talents. However, educational reform is affected by multiple and intertwined factors. This research, therefore, developed a system dynamics-based model of education reform to sort out relationships among all factors and predict the influence of several factors on AI talents output. Then, based on this model, series of experiments are carried out to find main factors affecting cultivation of AI talents. Results show that: 1)this model could accurately simulate trends of output ratio AI talents under different educational reform measures;2) Measures including teaching mode reform, improving the application rate of new teaching model, speeding up the construction of new disciplines in higher education, developing AI, improving ethics of AI, and strengthening the integration of AI and education could play significant roles in promoting cultivation of AI talents.

关键词： System dynamics education reform simulation artificial intelligent talents cultivation

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Gait Planning and Motion control Based on Vrep Simulation for Quadruped Robot 5

Gait Planning and Motion Control Based on Vrep Simulation fo...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhou, Linqi Chen, Zhihua Liu, Jun Liu, Zhi Chen, Yumeng Zhang, Liting Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Moe Key Lab of Nondestructive Testing Technology Nanchang330063 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing100081 China

ISBN: (纸本)9798350307320

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot's foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper. © 2023 IEEE.

关键词： Robot programming

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Metaverses-Based Parallel Oil Fields in CPSS: A Framework and Methodology

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2023年第4期53卷 2138-2147页

作者： Wang, Xingxia Cheng, Xiang Lu, Jingwei Kwan, Oliver Li, Shixing Ping, Zhixing Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automation State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Motion G Inc Singapore City 068898 Singapore North Automatic Control Technol Inst Taiyuan 030006 Peoples R China

Aiming to provide a novel paradigm of oil fields, metaverses-based parallel oil fields are proposed in this article. Compared with the existing smart/intelligent oil fields in cyber-physical systems (CPS), parallel oil fields can take human factors into full consideration and expand the operation space to cyber-physical-social systems (CPSS), which can be regarded as the abstract and scientific explanation of metaverses. In the proposed parallel oil fields, there are three kinds of workers (human workers, digital workers, and robotic workers) coordinating to construct a more reliable and intelligent oil field. Furthermore, the framework and methodology of parallel oil fields are illustrated by parallel systems and the artificial systems, computational experiments, and parallel executions (ACP) approach. Based on the proposed framework, parallel oil fields are capable of generating a more trustworthy artificial system and guaranteeing the realization of the 6S (safety, security, sustainability, sensitivity, service, and smartness) goal. Finally, based on dynamometer cards, fault diagnosis of sucker rod pumping systems (SRPS) is investigated in parallel oil fields.

关键词： Artificial systems computational experiments and parallel executions (ACP) approach Cyber-physical-social systems (CPSS) digital workers fault diagnosis metaverses-based parallel oil fields parallel systems

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MetaSocieties in Metaverse: MetaEconomics and Metamanagement for MetaEnterprises and MetaCities

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2022年第1期9卷 2-7页

作者： Wang, Fei-Yue Qin, Rui Wang, Xiao Hu, Bin Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Lanzhou Univ Sch Informat Sci & Engn Gansu Prov Key Lab Wearable Comp Lanzhou 730000 Gansu Peoples R China

Welcome to the first issue of the IEEE Transactions on Computational Social systems (TCSS) of 2022. We would like to take this opportunity to express our sincere thanks to our associate editors, reviewers, authors, and readers for your great support and effort devoted to IEEE TCSS. Happy New Year to you all, and cheers to health, happiness, and high-producing in 2022!

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Real-time In-situ Defect Detection in 3D Printing of Continuous Fiber-Reinforced Composites 4

Real-time In-situ Defect Detection in 3D Printing of Continu...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Yue, Zhijian Shen, Zhen Dong, Xiangyang Fang, Qihang Wang, Weixing Dong, Xisong Xiong, Gang Wang, Fei-Yue University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Beijing100190 China Qingdao Academy of Intelligent Industries Intelligent Manufacturing Center Qingdao266109 China Chinese Academy of Sciences Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Dongguan523808 China Chinese Academy of Sciences State Key Laboratory for Management and Control for Complex Systems Institute of Automation Beijing100190 China

ISBN: (纸本)9798350349252

With the development of continuous fiber-reinforced composites (CFRCs) 3D printing technology, timely, efficient and accurate detection of fiber path defects is essential for ensuring product quality and performance. However, challenges still need to be addressed in this field, such as inadequate training data coverage and the complexity of fiber path structures. These factors hinder the capability of traditional methods to accurately assess the status of printed products. Therefore, developing accurate and robust fiber path defect detection techniques is crucial for CFRCs 3D printing technology. In this paper, we propose a precise detection method for fiber path defects in CFRCs 3D printing using the YOLOv7 object detection model combined with a Squeeze-and-Excitation (SE) attention mechanism. By introducing the SE attention mechanism, we enhance the perception capability of the YOLOv7 model for crucial features, thereby improving the accuracy of fiber path defect detection. The experimental results show that the YOLOv7 model, when augmented with an attention mechanism, achieves an average accuracy of 93.9% in identifying fiber path defects during the printing process. Compared to models without this attention mechanism, the results show that there is 10.7% increase, with a notably enhanced learning capacity during the training phase, which substantiates the efficacy and practicality of the proposed approach. © 2024 IEEE.

关键词： Fiber reinforced plastics

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Microfabrication of Li4SiO4 pebbles with complex pore structure via digital light processing: Accuracy control and properties optimizing

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2024年 54卷 1410-1421页

作者： Cai, Liang Tao, Sirong Shen, Zhen Wan, Li Liu, Ziao He, Xilin Zhang, Yingchun Univ Sci & Technol Beijing Sch Mat Sci & Engn 30 Xueyuan Rd Beijing 100083 Peoples R China Chinese Acad Sci Inst Automat Beijing Engn Res Ctr Intelligent Syst & Technol State Key Lab Management & Control Complex Syst 95 Zhongguancun E Rd Beijing 100190 Peoples R China Ten Dimens Guangdong Technol Co Ltd 33 Informat Rd Foshan 528225 Peoples R China

Li4SiO4 ceramic pebble is deemed as the most attractive tritium breeder for fusion reactor blanket. In this work, we fabricated a novel Li4SiO4 pebble with micrometer-scale pore structure by digital light processing to verify the feasibility of complex pore structure manufacturing for future breeders. The effects of processing parameters on printing accuracy, microstructure and mechanical properties of Li4SiO4 pebbles were investigated. For synthesizing the pure Li4SiO4 phase, the optimal stoichiometric ratio of Li2SiO3 to Li2CO3 was 1:1.09 in the premixed powder. The photosensitivity of dual-phase ceramic suspension was investigated according to an attenuation model, and the overgrowth was reduced to similar to 50 mu m by using the dimension formula. After optimizing the post-processing, the radial pore structure Li4SiO4 pebbles with excellent crush load (50.3 N, standard deviation = 4.4 N) and suitable open porosity (18.3 %) can be yielded. This work provides a fresh solution to control the pore structure of tritium breeding pebbles in an unprecedented micrometer scale.

关键词： Additive manufacturing Digital light processing Tritium breeder material Ceramic pebble Lithium orthosilicate

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How Simulation Helps Autonomous Driving: A Survey of Sim2real, Digital Twins, and Parallel Intelligence

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON intelligent VEHICLES 2024年第1期9卷 593-612页

作者： Hu, Xuemin Li, Shen Huang, Tingyu Tang, Bo Huai, Rouxing Chen, Long Hubei Univ Sch Artificial Intelligence Wuhan 430062 Peoples R China Hubei Univ Minist Educ Key Lab Intelligent Sensing Syst & Secur Wuhan 430062 Peoples R China Worcester Polytechn Inst Dept Elect & Comp Engn Worcester MA 01609 USA Beijing Huairou Acad Parallel Sensing Beijing 101499 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100864 Peoples R China Waytous Inc Beijing 100083 Peoples R China

Developing autonomous driving technologies necessitates addressing safety and cost concerns. Both academic research and commercial applications of autonomous driving vehicles require extensive simulation and real-world testing. The challenge lies in effectively transferring driving knowledge from the virtual simulation world to the reality world, known as the reality gap (RG). This gap arises due to differences in lighting, textures, vehicle dynamics, and agents' behaviors between the two environments. To address this issue, researchers have explored three main approaches: sim2real, digital twins (DTs), and parallel intelligence (PI) technologies. This article reviews these solutions and examines their applications and innovations in autonomous driving. Furthermore, we delve into the state-of-the-art algorithms, models, and involved simulators, and discuss the developmental process from sim2real to DTs and PI. The presentation also sheds light on the challenges and future perspectives in the development of sim2real, DTs, and PI in the field of autonomous driving.

关键词： Autonomous vehicles Digital twins Task analysis Metalearning Virtual reality Vehicle dynamics Solid modeling Autonomous driving sim2real digital twins parallel intelligence reality gap

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Modeling the dynamic impacts of maritime network blockage on global supply chains

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The Innovation 2024年第4期5卷 103-109,102页

作者： Shen Qu Yunlei She Qi Zhou Jasper Verschuur Lu-Tao Zhao Huan Liu Ming Xu Yi-Ming Wei Center for Energy and Environmental Policy Research Beijing Institute of TechnologyBeijing 100081China School of Management Beijing Institute of TechnologyBeijing 100081China Beijing Key Lab of Energy Economics and Environmental Management Beijing 100081China Oxford Programme for Sustainable Infrastructure Systems(OPSIS) Environmental Change InstituteUniversity of OxfordOX12JD OxfordUK State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084China School of Environment Tsinghua UniversityBeijing 100084China

Recent phenomena such as pandemics,geopolitical tensions,and climate change-induced extreme weather events have caused transportation network interruptions,revealing vulnerabilities in the global supply chain.A salient example is the March 2021 Suez Canal blockage,which delayed 432 vessels carrying cargo valued at$92.7 billion,triggering widespread supply chain *** ability to model the spatiotemporal ramifications of such incidents remains *** fill this gap,we develop an agent-based complex network model integrated with frequently updated maritime *** Suez Canal blockage is taken as a case *** results indicate that the effects of such blockages go beyond the directly affected countries and *** Suez Canal blockage led to global losses of about$136.9($127.5–$147.3)billion,with India suffering 75%of these *** losses show a nonlinear relationship with the duration of blockage and exhibit intricate trends post *** proposed model can be applied to diverse blockage scenarios,potentially acting as an earlyalert system for the ensuing supply chain ***,high-resolution daily data post blockage offer valuable insights that can help nations and industries enhance their resilience against similar future events.

关键词： chains valued extreme

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