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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Huijie Dong Chunyang Zhao Tiezhu Qiao Jian Wang Di Chen Yan Meng Junzhi Yu Ministry of Education Key Laboratory of Advanced Transducers and Intelligent Control System Taiyuan University of Technology Taiyuan China Institute of Automation Laboratory of Cognitive and Decision Intelligence for Complex System Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang China

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named ‘CourierFish’. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks.

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Concept, Principle, and Modeling of Driving Risk Entropy Based on Human-Vehicle-Road Coupling Model for Autonomous Vehicle

SSRN

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SSRN 2024年

作者： Gao, Hongbo Yang, Hanqing Zhu, Juping Su, Huiping Wang, Ning Xie, Liping Li, Keqiang Department of Automation University of Science and Technology of China Hefei230026 China Institute of Advanced Technology University of Science and Technology of China Hefei230088 China School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore Chongqing College of Mobile Communication Chongqing400044 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing100084 China

Driving risk entropy, based on entropy law, is an innovative concept proposed for intelligent driving systems. The concept deals with the driving risks caused by the human-vehicle-road system from the driving information obtained;however, driving risks are difficult to assess due to many influencing factors and great uncertainty. The risk entropy model of vehicles is visualized by introducing the concept of basic isotropic risk elliptic line (BIREL). Further incorporating the concept of information entropy, risk entropy models for vehicle interaction and vulnerable participants are established, and the risk entropy model for roads is developed using raster coordinates. Ultimately, a three-dimensional driving risk entropy model is constructed based on the human-vehicle-road coupling model, with appropriate weights assigned to each parameter through the DDPG algorithm. Experimental results demonstrate the effectiveness of the driving risk entropy model. © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Innovative Competency-Based Electrical engineering Curriculum 54

Innovative Competency-Based Electrical Engineering Curriculu...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Rehder, Gustavo P. Serrano, Ariana L. C. Grimoni, José B. Brandão, Anarosa A. F. Silva, Magno M. T. Moriya, Henrique T. Panazio, Cristiano M. Barbero, Edson Alayo, Marco I. Gianesi, Irineu G. N. Seabra, Antonio C. Universidade de São Paulo Electronic Systems Department The Escola Politécnica São Paulo Brazil Universidade de São Paulo Electric Automation and Energy Dept. The Escola Politécnica São Paulo Brazil Universidade de São Paulo Computer Engineering and Digital Systems Department The Escola Politécnica São Paulo Brazil Universidade de São Paulo Telecommunications and Control Dept. The Escola Politécnica São Paulo Brazil Á lvares Penteado School of Commerce Foundation São Paulo Brazil Instituto Mauá de Tecnologia São Paulo Brazil

ISBN: (纸本)9798350351507

The Electrical engineering undergraduate program of the Escola Politécnica of the Universidade de São Paulo has created an alternative innovative curriculum path for its freshmen students in 2024. The Competency-based Path emphasizes the development of competencies and skills for the unprecedented technological advancements that necessitate a holistic education for future electrical engineers, preparing them with practical skills for real-world challenges. The program was designed using an innovative methodology and centers around semester-long or year-long integrative projects. These projects bridge the gap between theory and practice, as students deal with real-world challenges while fostering social responsibility. © 2024 IEEE.

关键词： Students

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Magnetic Field and Radial Force Analysis of Six-Phase Rotary Machine

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Guidance,Navigation and control 2022年第3期2卷 48-62页

作者： Ziwei Dong Liang Yan Chris Gerada School of Automation Science and Electrical Engineering Beihang University Science and Technology on Aircraft Control Laboratory Beihang University Ningbo Institute of Technology Beihang University Department of Electrical and Electronic Engineering University of Nottingham

Six-phase permanent magnet synchronous machine and the control system are also widely used in industry, precision instruments and aerospace. However, most PMSMs employ magnet patterns either in alternatively radial magnetization or Halbach array, which may constrain the performance improvement in a certain degree. Therefore, a novel six-phase trapezoidal Halbach magnet array(THMA) is proposed in this paper. Six-phase permanent magnet synchronous machines(PMSMs) can reduce the harmonic components of magnetic flux in air gap, and decrease the iron loss and electromagnetic vibration caused by harmonic torque. Thus, it helps to improve the working efficiency and depress the torque ripple of the electrical machine. Dual three-phase windings are employed for the stator design to further improve the power density and reliability of the machine. Six-phase vector model of the machine is built based on dual dq control. It can minimize the electric coupling, magnetic coupling and thermal coupling. The radial electromagnetic force of the machine under load or no load is extracted, then the harmonic decomposition of the radial electromagnetic force for the spatial with time Fourier decomposition is carried out to obtain the force amplitude of different orders which is conducive to analyze the vibration characteristics of the machine.

关键词： Six-phase permanent magnet synchronous machine radial electromagnetic force Fourier analysis

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Raman microscopic measurement of materials used on banknotes

Raman microscopic measurement of materials used on banknotes

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Circuits, systems, Communications and Computers (CSCC), International Conference on

作者： Hana Tomášková Vladimír Vašek Department of electronic and measurements Faculty of Applied informatics Tomas Bata University in Zlin Zlín Czech Republic Department of automation and control engineering Faculty of Applied informatics Tomas Bata University in Zlin Zlín Czech Republic

ISBN: (纸本)9781665481878

The successful verification of the authenticity of banknotes, or the detection of counterfeits, is based on the combination of an effective measuring system and computer technology. In this paper, a modern diagnostic method Raman microscopy together with an exploratory tool for processing and interpreting multi-dimensional datasets, and cluster analysis, are used to study structural differences between paper and orange ink used on genuine banknotes. Six currencies of European countries were selected for this study: Croatian kuna, Czech crown, euro, Great British Pound, Polish zloty, and Swiss franc. Raman microscopy offers non-destructive, rapid analysis without any sample preparation and pre-processing, with the potential to recognize structural modification of substances, together with the advantages of optical microscopy. Cotton fibres, $\text{TiO}_{2}$ in two different modifications, and other additives are successfully identified within the spectra. The patterns found in mathematically processed Raman data, especially between the paper, indicate both, the similarities and differences across the various banknotes, even of the same currency. The results serve as a base of the spectral database for authenticity control of banknotes and classification of the materials used.

关键词： Optical fibers Optical microscopy Databases Statistical analysis Microscopy Process control Ink

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Crowdsourced GNSS Satellite SNR in Degraded Environments for Dependability Improvement 22

Crowdsourced GNSS Satellite SNR in Degraded Environments for...

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22nd International Conference on Electromagnetics in Advanced Applications, ICEAA 2021

作者： Sun, Hao Lu, Debiao Cai, Baigen Xiao, Yu Beijing Jiaotong Univ. Beijing Eng. Research Center of Emc and Gnss Technology for Rail Transport School of Electronic and Information Engineering Frontiers Science Center for Smart High-speed Railway System Beijing China Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety School of Electronic and Information Engineering Frontiers Science Center for Smart High-speed Railway System Beijing China Aalto University School of Electrical Engineering Department of Communications and Networking Espoo Finland

ISBN: (纸本)9781665413862

Global Navigation Satellite systems (GNSS) localization uses time of arrival (TOA) to measure the distance between satellite and rover antenna. The key for TOA technique is the signal propagation should be straight geometrically. However, when the train runs in harsh environments, the GNSS signal quality can be degraded due to obstacles. GNSS signals are usually blocked by buildings and other obstacles, resulting in reflection and reflection, which leads to multipath positioning errors of LOS and NLOS. In the case of LOS multipath error, the GNSS receiver tracks the direct and reflected / diffracted composite signal, and the reflected / diffracted signal affects the correlation function tracking loop of the direct signal in GNSS. In the case of NLOS multipath error, GNSS receiver directly tracks reflected or diffracted signal because there is no direct satellite signal. In both cases, the multipath signal will have a large noise error range which is reflected in the change of SNR. In the GNSS solution, various GNSS receivers are used to obtain the SNR of each satellite to achieve the fully coverage of the satellite signal reception quality. Thus with limited GNSS receiver observation results, of the crowdsourcing of NLOS signal inspection will deliver the observation results in a more convenient way. In the open environment scenario, the relationship between elevation angle and SNR can be fitted by a linear function. However, in GNSS signal reception degraded environments (urban canyon etc.), The SNR at the elevation angle of the occlusion boundary will be drastically reduced. This will give us the boundary of the occlusion range. Based on this principle, we can map the environmental characteristics of different sections of the railway. The railway environment can generally be divided into open scenario, road cutting scenario, half sky scenario, urban canyon scenario and tunnel scenario. 5 typical scenario all have distinct environmental characteristics. By matching

关键词： Satellites

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Global Finite-Time Stabilization for a Chain of Integrators in the Presence of Actuator Saturation by Homogeneous Feedback

Global Finite-Time Stabilization for a Chain of Integrators ...

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IEEE Conference on Decision and control

作者： Tan Hou Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai P. R. China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA USA Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai P. R. China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA USA

This paper considers the problem of globally stabilizing a chain of integrators with actuator saturation in finite time. The proposed method is adapted from an existing scheduled low gain approach by relaxing the range of the value of the low gain parameter. Due to the special structure of the considered system, the proposed feedback law not only results in finite-time stability but also is homogeneous in the whole state space. The homogeneity of the proposed feedback law allows its implementation through the discretization of a compact set of the state space and thus obviation from numerical difficulties in the existing scheduled low gain design. A numerical example is presented to validate our theoretical results and demonstrate that our approach achieves faster convergence than the existing methods.

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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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GCBF: Grouped Cross-Band Fusion Network for Multispectral Scene Classification

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Li, Jin Liu, Yu Zhao, Wenda Jiang, Zhizhuo Wang, Xueqian Zheng, Bolun Tsinghua University Shenzhen International Graduate School Shenzhen 518055 China Tsinghua University Department of Electronic Engineering Beijing 100084 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education School of Information and Communication Engineering Dalian 116024 China Hangzhou Dianzi University School of Automation Hangzhou 310018 China

Remote sensing scene classification is a crucial task for remote sensing image interpretation. Existing multispectral scene classification methods have overlooked the interrelationships between different spectral bands, which limits the mining of complementary information within the images. Addressing this issue, we propose a grouped cross-band fusion (GCBF) network for remote sensing multispectral scene classification to take full advantage of complementary information between various spectral bands. Firstly, we separate the various bands of the given multispectral image into different groups to better capture the characteristics of each spectral band. Then, we use the existing UniFormer as a feature extractor to learn the representations of red, green, and blue (RGB) bands. For the spectral bands other than RGB, we propose a new network called multi-stage grouped spectral feature extraction (MGSFE) network to learn discriminative representations. We also draw inspiration from the band combination in the field of remote sensing and introduce a cross-band attention fusion (CBAF) module designed to adaptively merge features from both the RGB bands and other spectral bands. Extensive experiments on three widely used remote sensing multispectral scene classification datasets of BigEarthNet, SEN12MS, and EuroSAT demonstrate the superiority of our proposed method compared with several state-of-the-art (SOTA) methods. © 1980-2012 IEEE.

关键词： Cross-band attention multispectral image remote sensing scene classification

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Energy Management Based on Multi-Agent Deep Reinforcement Learning for A Multi-Energy Industrial Park

arXiv

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arXiv 2022年

作者： Zhu, Dafeng Yang, Bo Liu, Yuxiang Wang, Zhaojian Ma, Kai Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China

Owing to large industrial energy consumption, industrial production has brought a huge burden to the grid in terms of renewable energy access and power supply. Due to the coupling of multiple energy sources and the uncertainty of renewable energy and demand, centralized methods require large calculation and coordination overhead. Thus, this paper proposes a multi-energy management framework achieved by decentralized execution and centralized training for an industrial park. The energy management problem is formulated as a partially-observable Markov decision process, which is intractable by dynamic programming due to the lack of the prior knowledge of the underlying stochastic process. The objective is to minimize long-term energy costs while ensuring the demand of users. To solve this issue and improve the calculation speed, a novel multi-agent deep reinforcement learning algorithm is proposed, which contains the following key points: counterfactual baseline for facilitating contributing agents to learn better policies, soft actor-critic for improving robustness and exploring optimal solutions. A novel reward is designed by Lagrange multiplier method to ensure the capacity constraints of energy storage. In addition, considering that the increase in the number of agents leads to performance degradation due to large observation spaces, an attention mechanism is introduced to enhance the stability of policy and enable agents to focus on important energy-related information, which improves the exploration efficiency of soft actor-critic. Numerical results based on actual data verify the performance of the proposed algorithm with high scalability, indicating that the industrial park can minimize energy costs under different demands. © 2022, CC BY-NC-ND.

关键词： Multi agent systems

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