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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Liu, Xiao Chen, Luefeng Wu, Min Cao, Weihua Lu, Chengda Pedrycz, Witold School of Automation China University of Geosciences Wuhan China School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Department of Computer Engineering Sariyer Istanbul34396 Turkey

Changes in coal seam hardness cause fluctuations in the feed resistance at the drill bit during the drilling process, leading to unstable feeding speed. This paper proposes a robust dynamic output feedback controller to suppress disturbances caused by the variations in coal seam hardness in the feed system. Firstly, an unknown parameter measuring coal seam hardness is introduced, and an uncertain model of the feeding system is established based on the finite element model of the drill string. By designing weighted functions based on industrial field requirements and constructing a generalized plant, the controller achieves loop shaping, reducing the low-frequency impact of coal seam hardness variations on the feed system and suppressing the systems resonance peak. Simulation results demonstrate that the controller effectively suppresses parameter variations and external disturbances caused by changes in coal seam hardness, achieving stable control of the drilling speed. © 2024 IEEE.

关键词： Robust control

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Adaptive Absolute-Relative Rating for Noise Rejection in Behavioral Cloning based on Tsallis Statistics

Adaptive Absolute-Relative Rating for Noise Rejection in Beh...

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IEEE/SICE International Symposium on System Integration

作者： Taisuke Kobayashi Tadayoshi Aoyama National Institute of Informatics (NII) Graduate University for Advanced Studies (SOKENDAI) Tokyo Japan Department of Micro-Nano Mechanical Science and Engineering Graduate School of Engineering Nagoya University Nagoya Japan

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

In robot control from demonstrations, a sufficient dataset cannot be collected for many of the tasks that require experts with qualifications to special skills. Unfortunately, insufficient expert dataset would manifest various types of noise hidden in it. Since adding data is difficult as well, offline imitation learning needs to be robust to such a noise. In the conventional work, a behavioral cloning method based on Tsallis statistics has been developed. However, it weights each data with absolute rating with a fixed threshold, which would fail to imitate coarse/diverse motions. Therefore, this paper improves the conventional method by adding the function of relative rating for each data, which should enable robots to imitate non-noisy data even from coarse/diverse motions. This function can be obtained from a different derivation way of the optimization problem with Tsallis statistics. By integrating it with the conventional derivation way, the proposed method can adjust between the absolute and relative ratings. Finally, for more convenience, we design optimization tricks for the hyperparameters to maximize the variance of weights with avoiding extremely large weights. In numerical simulations and real-robot experiments, we demonstrate the robustness of the proposed method.

关键词： Sensitivity Imitation learning Noise Robot control Cloning System integration Numerical simulation Robustness Optimization Qualifications

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Mobile Robot Manipulator Localization in Indoor Environments for Object Picking Tasks

Mobile Robot Manipulator Localization in Indoor Environments...

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International Conference on control and Robots (ICCR)

作者： Yunfan Xie Goragod Pongthanisorn Shin-ichiro Kaneko Genci Capi Dept. of Mechanical Eng. Graduate School of Science and Engineering Hosei University Tokyo Japan Department of Electrical and Control Systems Engineering National Institute of Technology Toyama College Toyama Japan

ISBN: (数字)9798331518158

ISBN: (纸本)9798331518165

In dynamic and unpredictable work environments such as manufacturing, logistics, and automated warehouses, achieving high-precision self-localization estimation for efficient object picking are critical challenges for mobile robots. Ensuring accuracy and adaptability is essential for their successful operation. This paper presents a new method that integrates RGB cameras with Contrastive Learning (CL) for self-localization estimation and advanced object picking for mobile manipulators. The effectiveness of the proposed method for location estimation in object picking is verified in indoor environments.

关键词： Adaptation models Accuracy Robot vision systems Estimation Contrastive learning Predictive models Manipulators Robustness Indoor environment Mobile robots

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On Convergence in Distribution of Stein's Unbiased Risk Hyper-parameter Estimator for Regularized System Identification 41

On Convergence in Distribution of Stein's Unbiased Risk Hype...

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第41届中国控制会议

作者： Yue Ju Tianshi Chen Biqiang Mu Lennart Ljung School of Data Science and Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and System ScienceChinese Academy of Sciences Division of Automatic Control Department of Electrical EngineeringLink?ping University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Asymptotic theory for the regularized system identification has received increasing interests in recent *** this paper,for the finite impulse response(FIR) model and filtered white noise inputs,we show the convergence in distribution of the Stein's unbiased risk estimator(SURE) based hyper-parameter estimator and find factors that influence its convergence *** particular,we consider the ridge regression case to obtain closed-form expressions of the limit of the regression matrix and the variance of the limiting distribution of the SURE based hyper-parameter estimator,and then demonstrate their relation numerically.

关键词： Asymptotic theory Stein's unbiased risk estimator Hyper-parameter estimator Regularized system identification

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Metal matrix nanocomposites in tribology: Manufacturing, performance, and mechanisms

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Friction 2022年第10期10卷 1596-1634页

作者： Shuaihang PAN Kaiyuan JIN Tianlu WANG Zhinan ZHANG Long ZHENG Noritsugu UMEHARA Department of Mechanical and Aerospace Engineering University of California Los Angeles(UCLA)Los AngelesCA 90095USA Physical Intelligence Department Max Planck Institute for Intelligent SystemsStuttgart 70569Germany Stake Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Bionic Engineering(Ministry of Education) College of Biological and Agricultural EngineeringJilin UniversityChangchun 130022China Micro-Nano Mechanical Science Laboratory Department of Micro-Nano Mechanical Science and EngineeringGraduate School of EngineeringNagoya UniversityChikisa-ku Furo-choNagoyaAichi 464-8601Japan

Metal matrix nanocomposites(MMNCs)become irreplaceable in tribology industries,due to their supreme mechanical properties and satisfactory tribological ***,due to the dual complexity of MMNC systems and tribological process,the anti-friction and anti-wear mechanisms are unclear,and the subsequent tribological performance prediction and design of MMNCs are not easily possible:A critical up-to-date review is needed for MMNCs in *** review systematically summarized the fabrication,manufacturing,and processing techniques for high-quality MMNC bulk and surface coating materials in ***,important factors determining the tribological performance(mainly anti-friction evaluation by the coefficient of friction(CoF)and anti-wear assessment with wear rate)in MMNCs have been investigated thoroughly,and the correlations have been analyzed to reveal their potential coupling/synergetic roles of tuning tribological behavior of *** importantly,this review combined the classical metal/alloy friction and wear theories and adapted them to give a(semi-)quantitative description of the detailed mechanisms of improved anti-friction and anti-wear performance in *** guarantee the universal applications of these mechanisms,their links with the analyzed influencing factors(e.g.,loading forces)and characteristic features like tribo-film have been *** approach forms a solid basis for understanding,predicting,and engineering MMNCs’tribological behavior,instead of pure phenomenology and experimental ***,the pathway to achieve a broader application for MMNCs in tribo-related fields like smart materials,biomedical devices,energy storage,and electronics has been concisely discussed,with the focus on the potential development of modeling,experimental,and theoretical techniques in MMNCs’tribological *** general,this review tries to elucidate the complex tribo-performances of MMNCs in a fundamentally universal yet straightfor

关键词： metal matrix nanocomposites nanophases tribology manufacturing processes anti-wear performance strengthening effects anti-wear mechanisms

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A Robust Path Planning of Messenger UAV for Air-Ground Coordination Under Road Network Constraints

A Robust Path Planning of Messenger UAV for Air-Ground Coord...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Wang, Yuyang Xin, Bin Ding, Yulong Yin, Zhen He, Bin School of Automation Beijing Institute of Technology Beijing100081 China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing100081 China Tongji University Department of Control Science and Engineering Shanghai China

ISBN: (纸本)9781665481090

This paper addresses the path planning problem for unmanned aerial vehicle (UAV), where a UAV serves as a messenger to periodically traverse over road-constrained ground vehicles (GVs) to relay information. The GVs may not move on the road network with the velocities agreed with the UAV due to their movement uncertainties. The UAV path planning problem can be formulated as the Dynamic Dubins Traveling Salesman Problem with Uncertain Neighborhood (DDTSPUN). To address the uncertainty in GVs motion, we define robust neighborhoods and corridors and prove that the UAV visiting these areas can revisit GVs reliably, thus transforming DDTSPUN into a Revisit-time-constrained Dubins Traveling Salesman Problem with Neighborhood (RDTSPN). To address the RDTSPN, we propose an online heuristic path planning algorithm. This algorithm incorporates a gradient-based method for visiting robust neighborhoods and a sampling-based search strategy along robust corridors to obtain the Dubins paths of UAV that achieve the robust visit for each GV. Finally, computational experiments demonstrate its advantage over other benchmark algorithms in obtaining the shortest path satisfying UAV curvature constraints, and ensuring robust access to all GVs. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Posture control Problem of One-Link Torque Unit Manipulator – Application of Reaction Wheel with Air Resistance

Posture Control Problem of One-Link Torque Unit Manipulator ...

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SICE Annual Conference

作者： Ryota Hayashi Yasuyuki Setoyama Tetsuya Kinugasa Koji Yoshida Koichi Osuka Department of Mechanical Systems Engineering Okayama University of Science Okayama Japan Department of Electronic Control Engineering N. I. T. Kagoshima College Kagoshima Japan Graduate School of Engineering Osaka University Osaka Japan

ISBN: (数字)9784907764838

ISBN: (纸本)9798331544461

In this research, we study on posture control of a planar one-link torque unit manipulator which has a revolute joint with viscous friction. The torque unit is an easy maintenance module that consists of a motor and a reaction wheel, and it can be set to an arbitrary position of the link as an actuator to control the angle of the rotating link with free joint. However, the system of a planar one-link torque unit manipulator has an uncontrollable mode. There arises a problem such that the angular momentum of the reaction wheel remains non-zero after controlling to a target angle of the link. Furthermore, it is essentially inevitable that the link of the manipulator goes back to the initial angle after stopping of the control. In this paper, we investigate the eigenvalues of the control system in order to understand these phenomena. Then, we consider using a reaction wheel with air resistance and show that the link of the manipulator can be controlled to an arbitrary target angle even though the system has an uncontrollable mode. We conclude that the air resistance of the reaction wheel functions as a kind of implicit control.

关键词： Resistance Torque Friction Wheels Manipulators control systems Motors Iron Eigenvalues and eigenfunctions Maintenance

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Differentially Private Online Federated Learning with Correlated Noise

Differentially Private Online Federated Learning with Correl...

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IEEE Conference on Decision and control

作者： Jiaojiao Zhang Linglingzhi Zhu Mikael Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Systems Engineering and Engineering Management Chinese University of Hong Kong

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We introduce a novel differentially private algorithm for online federated learning that employs temporally correlated noise to enhance utility while ensuring privacy of continuously released models. To address challenges posed by DP noise and local updates with streaming non-iid data, we develop a perturbed iterate analysis to control the impact of the DP noise on the utility. Moreover, we demonstrate how the drift errors from local updates can be effectively managed under a quasi-strong convexity condition. Subject to an $(\epsilon, \delta)$ DP budget, we establish a dynamic regret bound over the entire time horizon, quantifying the impact of key parameters and the intensity of changes in dynamic environments. Numerical experiments confirm the efficacy of the proposed algorithm.

关键词： Privacy Federated learning Heuristic algorithms Noise Signal processing algorithms Servers

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Exponential Weighted Moving Average-Based Variational Mode Decomposition Method for Fault Diagnosis of Vehicle Batteries 13

Exponential Weighted Moving Average-Based Variational Mode D...

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13th IEEE Data Driven control and Learning systems Conference, DDCLS 2024

作者： Wu, Penghao Tao, Hongfeng Tian, Engang Yin, Tangwen Chen, Hongtian Chen, Yiyang School of Mechanical and Electrical Engineering Soochow University Suzhou215137 China Jiangnan University Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Wuxi214122 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China

ISBN: (纸本)9798350361674

In recent years, the rapid advancement of electric vehicles has heightened concerns regarding the safety of high-energy batteries. Consequently, there has been a significant focus on the development of fault diagnosis technologies for batteries. Intelligent fault diagnosis (IFD), particularly data-driven approaches, represents a crucial methodology in addressing this concern. This paper proposes a data-driven approach, for IFD in high-energy batteries utilized in electric vehicles. The proposed Exponentially Weighted Average Variational Mode Decomposition (EWVMD) method overcomes these limitations by employing the exponential weighted moving average (EWMA) technique to smooth collected time-series voltage data. This process reduces noise, accentuates abnormal change trends, and yields secondary data with enhanced features. Subsequently, variational mode decomposition (VMD) is applied to the secondary data. The resulting decomposed sub-mode curves (intrinsic mode functions - IMFs) and the change trends of the residual curve, in conjunction with a fault threshold tailored to actual working conditions, are utilized to ascertain the occurrence of faults. Design verification experiments, the C42MSA electric vehicle power supply battery undergoes charging and discharging tests with injected faults at fixed intervals. The collected fault signals are then subjected to fault diagnosis using EWVMD. Results demonstrate the algorithm's superior detection effectiveness and increased sensitivity to fault signals compared to traditional methods. © 2024 IEEE.

关键词： Variational mode decomposition

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