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Annual Conference of Industrial Electronics Society

作者： Keita Shimamoto Toshiyuki Murakami Tsukuba Research Laboratory YASKAWA Electric Corporation Ibaraki Japan Graduate School of Science and Technology Keio University Yokohama Japan Department of System Design Engineering Keio University Yokohama Japan

This paper presents a hybrid position/force control with equivalent mass matrices for position-and-force-sensorless manipulators and the evaluation of the control system. Position and force estimation methods in the controller are cascaded to estimate the position and force according to the respective characteristics of the electrical and mechanical systems. The proposed controller is designed to reduce vibration of the force control axes' motion from the cross-coupling factors of the dq-axis inductance, which cause position estimation error, and the cross-coupling effects among control axes from equivalent mass matrices, which expresses the relationship between the workspace force and acceleration. The position estimation based on the voltage equation, including the cross-coupling factors, derives compensation terms of the estimation error. The cross-coupling effects between position and force control axes in the equivalent mass matrices are designed to suppress the undesired force response vibrations. The experimental results show that the proposed system kept contact with an object during the rubbing motion by a 4-degree-of-freedom manipulator without position and force sensors. The utilized equivalent mass matrix reduced the force vibration caused by the vibration of the position estimation.

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Anti-Fatigue Nanomechanics in the Pre-Cracked Graphene-Copper Artificial Nacre Under Cyclic Tension

SSRN

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SSRN 2023年

作者： Liu, Xiaoyi Xu, Yunfei Shi, Jinchun Zhu, YinBo Zhang, Sen Wu, HengAn Mechanics+X Laboratory Chengdu Development Center of Science and Technology China Academy of Engineering Physics Chengdu610200 China CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern Mechanics CAS Center for Excellence in Complex System Mechanics University of Science and Technology of China Hefei230027 China

The fatigue performance of pre-cracked graphene-copper artificial nacre (GrCu nacre) under cyclic tensile loading is investigated using theoretical analysis and molecular dynamics (MD) simulations. Mechanical models are proposed to describe the fatigue performance of GrCu nacre, which agree well with MD simulations. Compared with nanocomposites consisting of large graphene sheets, graphene fragments cannot improve the ultimate strength of GrCu nacre, but significantly improve its fatigue limit. This anti-fatigue effect is dominated by the graphene-copper interfaces with van der Waals interactions, which can be adjusted by tailoring the architectural parameters of GrCu nacre. The ultimate strength of nacre decreases as the volume fraction of graphene increases. The fatigue limit of GrCu nacre decreases as the length of graphene fragments increases, and can be approximately described by a quadratic function of interlayer repeat spacing. An anomalous weakening effect occurs when the in-plane distance between graphene fragments is less than 2 nm, while this effect can be ignored when it is higher than 2 nm. The fatigue ratio of common metals is ~0.4, whereas that of GrCu nacre is generally higher than 0.9. These underlying mechanisms and theoretical models can improve the fundamental understanding of the fatigue performance of composites with incoherent interfaces, as well as the bottom-up design of graphene-metal nanocomposites. © 2023, The Authors. All rights reserved.

关键词： Molecular dynamics

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Trajectory Planning for Formation Variation of UGVs in Cluttered Environment

Trajectory Planning for Formation Variation of UGVs in Clutt...

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International Conference on Intelligent Transportation

作者： Jie Cheng Ruishuang Chen Zhihui Liang Shuan Ding Zaiyue Yang Shenzhen Key Laboratory of Control The-ory and Intelligent Systems School of System Design and Intelligent Manufacturing Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology (SUSTech) Shenzhen China

The problem of trajectory planning for formation variation of unmanned ground vehicles (UGVs) is challenging due to the coupled non-collision constraints that apply to multiple vehicles. To address this issue, an innovative frame-work based on the alternating direction method of multipliers (ADMM) is proposed in this paper. The framework decouples complex constraints into two categories: individual constraints and mutual constraints. The former category involves dynamic, formation, and static obstacle constraints, which can be solved in parallel by each vehicle. Convex feasible set (CFS) algorithm is employed in this paper to simplify the static obstacle constraints. The latter category deals with collision avoidance among vehicles during the variation process and can be solved by nonlinear solvers. The convergence of the ADMM for the optimization problem is proved in this paper. Compared with solving the entire problem directly, the proposed framework reduces computation time and improves the quality of solution.

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Mixture of Experts for Intelligent Networks: A Large Language Model-enabled Approach

Mixture of Experts for Intelligent Networks: A Large Languag...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Hongyang Du Guangyuan Liu Yijing Lin Dusit Niyato Jiawen Kang Zehui Xiong Dong In Kim School of Computer Science and Engineering Nanyang Technological University Singapore Singapore State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China School of Automation Guangdong University of Technology and Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Singapore Department of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Optimizing various wireless user tasks poses a significant challenge for networking systems because of the expanding range of user requirements. Despite advancements in Deep Reinforcement Learning (DRL), the need for customized optimization tasks for individual users complicates developing and applying numerous DRL models, leading to substantial computation resource and energy consumption and can lead to inconsistent outcomes. To address this issue, we propose a novel approach utilizing a Mixture of Experts (MoE) framework, augmented with Large Language Models (LLMs), to analyze user objectives and constraints effectively, select specialized DRL experts, and weigh each decision from the participating experts. Specifically, we develop a gate network to oversee the expert models, allowing a collective of experts to tackle a wide array of new tasks. Furthermore, we innovatively substitute the traditional gate network with an LLM, leveraging its advanced reasoning capabilities to manage expert model selection for joint decisions. Our proposed method reduces the need to train new DRL models for each unique optimization problem, decreasing energy consumption and AI model implementation costs. The LLMenabled MoE approach is validated through a general maze navigation task and a specific network service provider utility maximization task, demonstrating its effectiveness and practical applicability in optimizing complex networking systems.

关键词： Wireless communication Energy consumption Navigation Computational modeling Logic gates Probability Throughput

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Correction to:Study on the resource utilization of high fluorine-containing organic waste through fluidized incineration

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Waste Disposal and Sustainable Energy 2023年第2期5卷 245-245页

作者： Wenhan Li Zengyi Ma Jianhua Yan Qianming Huang Xingjian Wen Zian Zhai Bochen Huang Shuang Wang Yongqiang Chen Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of ChinaChengdu610213China State Key Laboratory of Clean Energy Utilization Institute for Thermal Power EngineeringZhejiang UniversityHangzhou310027China Zhejiang Xianchuang Energy&Technology Co.Ltd Jinhua321000China

Correction to:Waste Disposal&Sustainable Energy(2022)4:117-129 https://***/10.1007/s42768-022-00101-7 The section Confict of interest'has been amended:'Jian-hua Yan is the Editor in-Chief of Waste Disposal&Sustain-able Energy.'The revised'Confict of interest'is as follows:Jianhua Yan is the Editor-in-Chief of Waste Disposal&Sustainable *** behalf of all authors,the corresponding author states that there is no conflict of interest.

关键词： Sustainable fluorine behalf

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Bioinspired hierarchical helical nanocomposite macrofibers based on bacterial cellulose nanofibers

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National science Review 2020年第1期7卷 73-83页

作者： Huai-Ling Gao Ran Zhao Chen Cui Yin-Bo Zhu Si-Ming Chen Zhao Pan Yu-Feng Meng Shao-Meng Wen Chuang Liu Heng-An Wu Shu-Hong Yu Division of Nanomaterials & Chemistry Hefei National Laboratory for Physical Sciences at the Microscale CAS Center for Excellence in Nanoscience Hefei Science Center of CAS Department of Chemistry University of Science and Technology of China CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern Mechanics CAS Center for Excellence in Complex System Mechanics University of Science and Technology of China

Bio-sourced nanocellulosic materials are promising candidates for spinning high-performance sustainable macrofibers for advanced applications. Various strategies have been pursued to gain nanocellulose-based macrofibers with improved strength. However, nearly all of them have been achieved at the expense of their elongation and toughness. Inspired by the widely existed hierarchical helical and nanocomposite structural features in biosynthesized fibers exhibiting exceptional combinations of strength and toughness, we report a design strategy to make nanocellulose-based macrofibers with similar characteristics. By combining a facile wet-spinning process with a subsequent multiple wet-twisting procedure, we successfully obtain biomimetic hierarchical helical nanocomposite macrofibers based on bacterial cellulose nanofibers, realizing impressive improvement in their tensile strength, elongation and toughness simultaneously. The achievement certifies the validity of the bioinspired hierarchical helical and nanocomposite structural design proposed here. This bioinspired design strategy provides a potential platform for further optimizing or creating many more strong and tough nanocomposite fiber materials for diverse applications.

关键词： bioinspired nanocomposite hierarchical helical macrofibers strength and toughness bacterial cellulose

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Building Energy Efficiency Assessment Base on Predict-Center Criterion Under Diversified Conditions

SSRN

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SSRN 2023年

作者： Liao, Xuechao Zheng, Xiujuan Ping, Zouwei Zhao, Haoyi Wang, Ning Zhang, Yong School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430080 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430080 China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan430080 China National Key Laboratory of Science and Technology on Vessel Integrated Power System Naval University of Engineering Wuhan430030 China WISDRI City Construction Engineering &Research Incorporation Ltd. Wuhan430030 China Changjiang Institute of Survey Planning Design and Research Wuhan430010 China

With the rapid expanding of urban economy and population, how to reduce the energy consumption and improve energy efficiency of public buildings has become a key issue for energy conservation and urban development. However, due to the diversity of building employing condition, energy consumption data often has problems with nonlinearity, outliers, and diversity, which will greatly reduce the accuracy of energy consumption prediction and energy conservation assessment. To overcome the above drawbacks, a regression prediction model of building energy consumption is designed, which cluster the same type of data characteristics to form a subset of equipment through Gaussian mixture clustering, and design the specific normalized adaptive loss function to determine the optimal control parameters of regression model. Furthermore, a novel predict-center energy efficiency evaluation criterion is proposed, and the cumulative distribution pattern is further statistically analyzed. Finally, the energy benchmark evaluation framework is proposed to determine the energy efficiency evaluation grade. Through comparative experimental analysis, it can be seen that the proposed prediction model can adapt to different types of building data, and have better prediction accuracy and convergence speed. The consistency and robustness of the benchmark evaluation framework and method are optimal. © 2023, The Authors. All rights reserved.

关键词： Energy utilization

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Orthogonal Geometry of Magneto-Optical Kerr Effect Enabled by Magnetization Multipole of Berry Curvature

arXiv

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arXiv 2024年

作者： Pan, Haolin Li, Han Huang, Jixiang Liu, Zheng Fang, Mingyue Yuan, Yanan Liu, Daxiang Hu, Xintong Peng, Wenzhi Liang, Zhenguo Chang, Xiao Sheng, Zhigao Chen, Xianzhe Wang, Lingfei Li, Qian Li, Peng Niu, Qian Gao, Yang Yang, Qinghui Hou, Dazhi International Center for Quantum Design of Functional Materials Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of China Hefei230026 China School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Microelectronics University of Science and Technology of China Hefei230026 China Department of Physics University of Science and Technology of China Hefei230026 China National Synchrotron Radiation Laboratory University of Science and Technology of China Hefei230026 China High Magnetic Field Laboratory Chinese Academy of Sciences Hefei230031 China Frontier Institute of Chip and System Fudan University Shanghai200000 China

The Magneto-Optical Kerr Effect (MOKE) is a fundamental tool in magnetometry, pivotal for advancing research in optics, magnetism, and spintronics as a direct probe of magnetization. Traditional MOKE measurements primarily detect the magnetization components parallel to the Poynting vector, which can only access the magnitude but not the direction of the orthogonal component. In this study, we introduce an orthogonal MOKE geometry in which the Kerr signal detects both the magnitude and direction of the magnetization component perpendicular to the Poynting vector. We demonstrate the broad applicability of this orthogonal geometry through the MOKE measurements in cubic ferromagnets and van der Waals ferromagnet. We theoretically show that the orthogonal MOKE geometry is enabled by the multipolar structure of Berry curvature in the magnetization space, which generally induces a Voigt vector orthogonal to the magnetization, thereby accounting for the unique magnetization angle dependence distinct from conventional MOKE. The establishment of the orthogonal MOKE geometry not only introduces a new paradigm for magneto-optical measurements but also provides a framework for exploring the magnetization multipoles of Berry curvature across the electromagnetic spectrum. Copyright © 2024, The Authors. All rights reserved.

关键词： Van der Waals forces

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design of Cooled Dual-Group Linked Continuous Zoom Hybrid Refractive-Diffractive system Based on Double-Layer Diffractive Element

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Guangxue Xuebao/Acta Optica Sinica 2025年第9期45卷

作者： Ma, Chengshuang Li, Ying Xue, Changxi Key Laboratory of Advanced Optical System Design and Manufacturing Technology of Jilin Province Changchun University of Science and Technology Jilin Changchun130022 China Department of Instrument Science and Technology Changchun University of Science and Technology Jilin Changchun130022 China School of Optoelectronic Engineering Changchun University of Science and Technology Jilin Changchun130022 China

Objective In recent years, with increasing demands for imaging optical systems and continuous advancements in manufacturing technologies, dual-band infrared zoom optical systems have been widely applied in various fields such as military reconnaissance, precision guidance, airborne electro-optical pods, aerospace, security, and night vision surveillance. Continuous zoom infrared lenses enable target searching over a wide field of view and rapid switching to a narrow field of view for precise tracking and observation. This capability is particularly advantageous for tracking high-speed moving targets, addressing the issue of losing targets during field-of-view switching in stepped zoom lenses. However, dual-band infrared zoom systems face challenges such as complex structures, difficult aberration correction, suboptimal image quality, and limited material selection. Therefore, developing a high-performance dual-band infrared zoom optical system is crucial for advancing imaging optical systems. Methods First, in the dual-band infrared range of 3.7‒4.8 μm and 8‒10 μm, a double-layer diffractive optical element (DOE) is designed using a method that maximizes polychromatic integrated diffraction efficiency (PIDE) considering angular-wavelength characteristics. The wavelengths corresponding to the maximum PIDE values are selected as the design wavelengths, and the corresponding microstructure height parameters are calculated. The designed double-layer DOE achieves a comprehensive PIDE of 98.29%, demonstrating high diffraction efficiency across the dual-band infrared range. Second, a dual-group linked zoom model is derived. Using this model, the component distances at different focal lengths are calculated. These parameters are then input into optical design software to develop a dual-band infrared zoom optical system with a continuous zoom range of 30‒300 mm. However, the initial system exhibits suboptimal image quality. Finally, the high-efficiency double-layer DOE is in

关键词： Thermography (imaging)

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Learning Pre-Grasp Manipulation of Flat Objects in Cluttered Environments using Sliding Primitives

Learning Pre-Grasp Manipulation of Flat Objects in Cluttered...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jiaxi Wu Haoran Wu Shanlin Zhong Quqin Sun Yinlin Li State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China Department of Automation University of Science and Technology of China Heifei China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Science Beijing China Science and Technology on Thermal Energy and Power Laboratory Wuhan China

Flat objects with negligible thicknesses like books and disks are challenging to be grasped by the robot because of the width limit of the robot's gripper, especially when they are in cluttered environments. Pre-grasp manipulation is conducive to rearranging objects on the table and moving the flat objects to the table edge, making them graspable. In this paper, we formulate this task as Parameterized Action Markov Decision Process, and a novel method based on deep reinforcement learning is proposed to address this problem by introducing sliding primitives as actions. A weight-sharing policy network is utilized to predict the sliding primitive's parameters for each object, and a Q-network is adopted to select the acted object among all the candidates on the table. Meanwhile, via integrating a curriculum learning scheme, our method can be scaled to cluttered environments with more objects. In both simulation and real-world experiments, our method surpasses the existing methods and achieves pre-grasp manipulation with higher task success rates and fewer action steps. Without fine-tuning, it can be generalized to novel shapes and household objects with more than 85% success rates in the real world. Videos and supplementary materials are available at https://***/view/pre-grasp-sliding.

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