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2022 Chinese Automation Congress, CAC 2022

作者： Liao, Zehua Wei, Qinglai Li, Hongyang University of Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems School of Artificial Intelligence Beijing China

ISBN: (纸本)9781665465335

As a distributed energy storage system, smart home energy (SHE) system can be used to reduce the consumption cost of household users. Aiming at the optimal control SHE systems, a novel multi-iteration adaptive dynamic programming (MIADP) method is constructed. The present algorithm introduces three iterations, namely, exterior iteration, local iteration and interior iteration, to ensure that the iterative Q-function converges to the optimal, and thus the optimal energy storage control scheme of the SHE system with solar energy is obtained. Finally, the present MIADP algorithm is illustrated by the experimental results. © 2022 IEEE.

关键词： Solar energy

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Evolution of Opinions with Estimation and Interference 41

Evolution of Opinions with Estimation and Interference

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第41届中国控制会议

作者： Yifa Liu Long Cheng State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The evolution of opinion is largely influenced by individual subjectivity,however,this is neglected in many studies about opinion *** paper analyzes the evolution of self-cognition and its impact on the spread of opinion from the perspective of individual ***,this paper considers the effect of external interference on the cluster by altering social interaction,and discusses the impact of demagoguery on individual self-cognition bias and polarization of the cluster.

关键词： Opinion dynamics Self-cognition Estimation

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Magnetic Microrobots Fabricated by Photopolymerization and Assembly

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Cyborg and Bionic systems 2023年第1期4卷 41-46页

作者： Xiyue Liang Yue Zhao Dan Liu Yan Deng Tatsuo Arai Masaru Kojima Xiaoming Liu Key Laboratory of Biomimetic Robots and Systems Ministry of EducationState Key Laboratory of Intelligent Control and Decision of Complex SystemBeijing Advanced Innovation Center for Intelligent Robots and Systemsand School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Center for Neuroscience and Biomedical Engineering The University of Electro-CommunicationsTokyo 182-8585Japan Department of Materials Engineering Science Osaka UniversityOsaka 560-8531Japan

Magnetic soft microrobots have great potential to access narrow spaces and conduct multiple tasks in the biomedical *** now,drug delivery,microsurgery,disease diagnosis,and dredging the blocked blood vessel have been realized by magnetic soft microrobots in vivo or in ***,as the tasks become more and more complex,more functional units have been embedded in the body of the developed magnetic *** magnetic soft microrobots with complex designed geometries,mechanisms,and magnetic orientation are now greatly challenging the fabrication of the magnetic *** this paper,we propose a new method combining photopolymerization and assembly for the fabrication of magnetic soft *** the micro-hand assembly system,magnetic modules with different shapes and materials are firstly arrayed with precise position and orientation ***,the developed photopolymerization system is employed to fix and link these modules with soft *** on the proposed fabrication method,3 kinds of soft magnetic microrobots were fabricated,and the fundamental locomotion was *** believe that the presented fabrication strategy could help accelerate the clinical application of magnetic microrobots.

关键词： Magnetic system precise

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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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Graph-based Selection-Activation Reinforcement Learning for Heterogenous Multi-agent Collaboration 43

Graph-based Selection-Activation Reinforcement Learning for ...

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43rd Chinese control Conference, CCC 2024

作者： Chen, Hao-Xiang Zhang, Xi-Wen Shen, Jun-Nan Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System School of Automation Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401135 China

ISBN: (纸本)9789887581581

In practical applications of multi-agent systems, agents are often heterogeneous, and each type of them typically has different task objectives. For heterogeneous multi-agent reinforcement learning (HMARL), the diversity of agent types and the unbalanced agent number of each type can lead to the curse of dimensionality and non-stationary. Moreover, the increase in the number of heterogeneous agents may result in slow convergence during training. This paper proposes a graph-based selection-activation reinforcement learning (GSARL) method for training heterogenous multi-agent collaboration strategies. It first constructs agents based on their types, then extracts the global adjacency matrices and the ally adjacency matrices from the agents' observations, and calculates the global feature matrices. Afterwards, GSARL utilizes hierarchical graph convolutional network to sequentially convolve the global information and ally information, obtaining action logits based on agent types. By using the neural topology graph and the selection-activation method, the optimal multi-agent collaboration configuration is obtained through combinatorial optimization. Experiments are conducted in an adversarial combat simulation environment involving collaborative Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs). Simulation results show that the proposed method can accelerate convergence while allowing that each type of heterogeneous agents can leverage its unique advantages. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Unmanned aerial vehicles (UAV)

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Parallel Manufacturing for Industrial Metaverses:A New Paradigm in Smart Manufacturing

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IEEE/CAA Journal of Automatica Sinica 2022年第12期9卷 2063-2070页

作者： Jing Yang Xiaoxing Wang Yandong Zhao The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Beijing SANBODY Technology Company LtdBeijing 214000China North Automatic Control Technology Institute Taiyuan 030006China

To tackle the complexity of human and social factors in manufacturing systems, parallel manufacturing for industrial metaverses is proposed as a new paradigm in smart manufacturing for effective and efficient operations of those systems, where Cyber-Physical-Social systems(CPSSs) and the Internet of Minds(Io M) are regarded as its infrastructures and the "Artificial systems", "Computational experiments"and "Parallel execution"(ACP) method is its methodological foundation for parallel evolution, closed-loop feedback, and collaborative optimization. In parallel manufacturing, social demands are analyzed and extracted from social intelligence for product R&D and production planning, and digital workers and robotic workers perform the majority of the physical and mental work instead of human workers, contributing to the realization of low-cost, high-efficiency and zero-inventory manufacturing. A variety of advanced technologies such as Knowledge Automation(KA), blockchain, crowdsourcing and Decentralized Autonomous Organizations(DAOs) provide powerful support for the construction of parallel manufacturing, which holds the promise of breaking the constraints of resource and capacity, and the limitations of time and space. Finally, the effectiveness of parallel manufacturing is verified by taking the workflow of customized shoes as a case,especially the unmanned production line named Flex Vega.

关键词： Parallel Manufacturing Digital Workers CPSS Smart Manufacturing Industrial Metaverses

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Trends and drivers of anthropogenic NOx emissions in China since 2020

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Environmental Science and Ecotechnology 2024年第5期21卷 287-293页

作者： Hui Li Bo Zheng Yu Lei Didier Hauglustaine Cuihong Chen Xin Lin Yi Zhang Qiang Zhang Kebin He Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration Institute of Environment and EcologyTsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084China State Environmental Protection Key Laboratory of Environmental Planning and Policy Simulation and Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental PlanningBeijing 100041China Laboratoire des Sciences du Climat et de l’Environnement LSCE/IPSLCEA-CNRS-UVSQUniversite Paris-SaclayGif-sur-YvetteFrance Center for Satellite Application on Ecology and Environment Ministry of Ecology and Environment of ChinaBeijing 100094China Institute of Future Human Habitats Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China

Nitrogen oxides(NOx),significant contributors to air pollution and climate change,form aerosols and ozone in the ***,timely,and transparent information on NOx emissions is essential for decision-making to mitigate both haze and ozone ***,a comprehensive understanding of the trends and drivers behind anthropogenic NOx emissions from Chinadthe world's largest emitterdhas been lacking since 2020 due to delays in emissions *** we show a consistent decline in China's NOx emissions from 2020 to 2022,despite increased fossil fuel consumption,utilizing satellite observations as constraints for NOx emission estimates through atmospheric *** reduction is corroborated by data from two independent spaceborne instruments:the TROPOspheric Monitoring Instrument(TROPOMI)and the Ozone Monitoring Instrument(OMI).Notably,a reduction in transport emissions,largely due to the COVID-19 lockdowns,slightly decreased China's NOx emissions in *** subsequent years,2021 and 2022,reductions in NOx emissions were driven by the industry and transport sectors,influenced by stringent air pollution *** satellite-based inversion system developed in this study represents a significant advancement in the real-time monitoring of regional air pollution emissions from space.

关键词： China's NOx emissions Pollution control Socio-economic drivers Atmospheric inversion

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Platform governance in the era of AI and the digital economy

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Frontiers of Engineering management 2023年第1期10卷 177-182页

作者： Xiaolong ZHENG Gang ZHOU Daniel Dajun ZENG The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence Chinese Academy of SciencesBeijing 100190China

1 Introduction Companies that supply online services such as Twitter,Weibo,and Taobao are known as platform companies(Gorwa,2019).Many top companies offer their services through platforms and use Internet technology to facilitate economic transactions,transmit information,connect people,and make predictions(Fenwick et al.,2019).Such platforms cover all areas of society,including politics(Gillespie,2017),labor relations,cultural production(Scholz,2016;van Doorn,2017),and consumption(Nieborg and Poell,2018).The rapid development of Internet technology has increased the influence of network *** platforms have changed the rules of global business operations and influenced the global political *** some high-profile negative events,calls for strengthening the regulation of online platforms and holding them accountable have been growing(Suzor,2019).

关键词： companies services operations

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DriveRP: RAG and Prompt Engineering Embodied Parallel Driving in Cyber-Physical-Social Spaces 4

DriveRP: RAG and Prompt Engineering Embodied Parallel Drivin...

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

作者： Huang, Jun Ma, Hao Zhang, Tengchao Lin, Fei Ma, Siji Wang, Xiao Wang, Fei-Yue Macau University of Science and Technology Faculty of Innovation Engineering China Anhui University School of Artificial Intelligence Hefei China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing China

ISBN: (纸本)9798350349252

In recent years, numerous technological advancements in Artificial Generative Intelligences (AGIs) have demonstrated significant potential to transform the intelligence acquisition mechanisms in connected autonomous vehicles (CAVs). Integrating technologies like ChatGPT into CAVs can enhance human-machine interactions. However, the emergence of such new traffic entities may introduce unforeseen hallucinations and complex risks that surpass our current understanding. To address these challenges, Retrieval-Augmented Generation (RAG) and prompt engineering technologies are being explored to enhance the reliability and safety of autonomous driving systems. RAG retrieves relevant contextual information, such as driving experiences and real-time road network status, from external databases to ensure that foundation models have access to accurate and timely data for informed decision-making. Prompt engineering optimizes the performance of large language models in autonomous driving systems by designing and refining prompts that guide the models' responses, thereby improving their relevance and accuracy in various driving scenarios. Together, these technologies enhance the robustness and trustworthiness of autonomous driving systems. This paper proposes DriveRP, a framework that integrates RAG and prompt engineering within the Descriptive-Predictive-Prescriptive Intelligence framework of Parallel Driving theory. DriveRP aims to enhance the safety and interpretability of autonomous vehicle trajectory planning, decision-making, and motion control, ultimately achieving the "6S"goals. Grounded in Digital Twins and Metaverse-embodied parallel driving theory, DriveRP provides the infrastructure and foundational intelligence for parallel driving with Multi-modal Large Lange Models(MLLMs). Additionally, the paper discusses future trends and potential research directions, focusing on the "6S"goals of parallel driving: Smart, Safe, Secure, Sensitive, Sustainable, and Serviceable. © 2

关键词： Intelligent systems

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Tissue Surface-enhanced Raman Spectroscopy Combined with Machine Learning Algorithms for Rapid Detection of Alveolar Echinococcosis 25

Tissue Surface-enhanced Raman Spectroscopy Combined with Mac...

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

作者： Huang, Jiahui Zheng, Xiangxiang Lv, Guodong Li, Xiaojing Wu, Guohua Xu, Liang Tianjin University of Technology Tianjin Key Laboratory of Complex System Control Theory and Application Tianjin China The First Affiliated Hospital of Xinjiang Medical University State Key Laboratory of Pathogenesis Prevention and Treatment of High Incidence Diseases in Central Asia Urumqi China Beijing University of Posts and Telecommunications School of Electronic Engineering Beijing China

ISBN: (纸本)9798350366600

Alveolar echinococcosis (AE) remains a serious worldwide public health problem as a very harmful human tapeworm disease. Rapid and accurate diagnosis of AE is crucial for treatment and postoperative recovery. This study explored the applicability of tissue surface Raman spectroscopy (SERS) combined with machine learning for rapid AE detection. Specifically, liver tissue section samples were obtained by creating an AE mouse model and SERS spectra were acquired. Five kinds of machine learning methods were used to construct AE diagnosis model, among which the linear kernel support vector machine (SVM) model had the best classification result, and the accuracy rate reached 95.7%. Then, the linear SVM model was subjected to feature significance analysis, which demonstrated that the biochemicals corresponding to the spectra of 641,716 and 1372 cm-1 might be potential biomarkers. Gaussian noise is further added to test the noise interference resistance of different machine learning algorithms, and it is found that SVM with Gaussian radial basis function (RBF) kernel function has better noise interference resistance. The results show that tissue SERS spectroscopy combined with SVM algorithm for rapid detection of AE has a promising application. © 2024 IEEE.

关键词： Raman scattering

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