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第35届中国控制会议

作者： LI Jing Jing Fengshui Li En Key Laboratory of Complex Systems and Intelligent Science Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781509009107

Arc welding robots are widely used in *** robots require highly-skilled workers doing time-consuming and tedious programming *** proposed new teaching system in this paper is aiming to simplify the programming process by adding a path point generation module,which depends on a RGB-D sensor to obtain the point cloud and generate path points for space curve *** advantage of this system is simplifying the teaching process,which is a step forward of realizing task-level *** system is used on an ordinary arc welding robot while not changing it,working as a plug-and-play type solution for easy *** this paper,the structure of this teaching system is *** architecture of important modules in the system is presented in *** example is showed that how this system is working.

关键词： Teaching system path generation point cloud Robot Operation System

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Pre-Equalization Aided Grant-Free Massive Access in Massive MIMO System

arXiv

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arXiv 2025年

作者： Wang, Yueqing Mei, Yikun Gao, Zhen Wan, Ziwei Ning, Boyu Mi, De Muhaidat, Sami School of Information and Electronics Beijing Institute of Technology Beijing100081 China MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing Institute of Technology Beijing100081 China Jiaxing314019 China Advanced Technology Research Institute Beijing Institute of Technology Jinan250307 China National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China School of Computing and Digital Technology Birmingham City University BirminghamB55JU United Kingdom KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi United Arab Emirates

The spatial diversity and multiplexing advantages of massive multi-input-multi-output (mMIMO) can significantly improve the capacity of massive non-orthogonal multiple access (NOMA) in machine type communications. However, state-of-the-art grant-free massive NOMA schemes for mMIMO systems require accurate estimation of random access channels to perform activity detection and the following coherent data demodulation, which suffers from excessive pilot overhead and access latency. To address this, we propose a pre-equalization aided grant-free massive access scheme for mMIMO systems, where an iterative detection scheme is conceived. Specifically, the base station (BS) firstly activates one of its antennas (i.e., beacon antenna) to broadcast a beacon signal, which facilitates the user equipment (UEs) to perform downlink channel estimation and pre-equalize the uplink random access signal with respect to the channels associated with the beacon antenna. During the uplink transmission stage, the BS detects UEs’ activity and data by using the proposed iterative detection algorithm, which consists of three modules: coarse data detection (DD), data-aided channel estimation (CE), and fine DD. In the proposed algorithm, the joint activity and DD is firstly performed based on the signals received by the beacon antenna. Subsequently, the DD is further refined by iteratively performing data-aided CE module and fine DD module using signals received by all BS antennas. Our simulation results demonstrate that the proposed scheme outperforms state-of-the-art mMIMO-based grant-free massive NOMA schemes with the same access latency. Simulation codes are provided to reproduce the results in this article: https://***/owenwang517/tvt-2025. Copyright © 2025, The Authors. All rights reserved.

关键词： Channel estimation

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Modeling of hysteresis in piezoelectric actuator using linear play operator adaptive filter

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key Engineering Materials 2015年 645卷 957-962页

作者： Xiong, Rui Liu, Xiangdong Shan, Fengmin Key Laboratory for Intelligent Control and Decision of Complex Systems Beijing China Automation College Beijing Institute of Technology Beijing China

Piezoelectric actuator(PEA) is widely applied in micro/nano positioning system. However, its inherent hysteresis limits its application. Modeling of hysteresis plays an important role in solving this problem. Linear play operators (LPO) adaptive hysteresis model is introduced in this paper. LPO operators are used to replace delay operators of adaptive transversal filter to compose a new serial structure of adaptive transversal filter model, and LMS (Least Mean Square) algorithm is used to adjust the weight values. As hysteresis loop of piezoelectric actuator is asymmetric and LPO operator is symmetric, a modified LPO (MLPO) adaptive filter is proposed for asymmetric hysteresis effect. At last, the two LPO filters are applied to model hysteresis characteristic of Piezoelectric actuator, and the modeling effect is verified via a micro-positioning system experiment platform based on Piezoelectric actuator. Experimental results show that the modified LPO filters can achieve better accurate hysteresis modeling. © (2015) Trans Tech Publications, Switzerland.

关键词： Hysteresis

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Research on Temperature Error Calibration Method of Fluxgate Sensor 11th

Research on Temperature Error Calibration Method of Fluxga...

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11th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2024

作者： Yang, Ruiping Ge, Jian Luo, Wang Hu, Xiangyun She, Jinhua Chugo, Daisuke Dong, Haobin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Faculty of Engineering Kwansai Gakuin University Osaka669-1330 Japan School of Geophysics and Geomatics China University of Geosciences Wuhan430074 China Hubei Subsurface Multi-scale Imaging Key Laboratory Wuhan430074 China School of Engineering Tokyo University of Technology Hachioji Tokyo192-0982 Japan

ISBN: (纸本)9789819647521

The fluxgate sensor is the most widely used sensor in vector magnetic measurement. However, during long-term continuous observation, the fluxgate sensor will produce large measurement errors due to changes in ambient temperature. This paper proposes a temperature calibration method for the fluxgate sensor based on polynomial fitting to address the temperature error of fluxgate sensors. First, the effect of temperature on the performance indicators of the fluxgate sensor was analyzed. Second, according to the existing temperature-magnetic field data, a temperature calibration model of the fluxgate sensor was constructed. And compared it with other temperature calibration method, the result shows that the proposed temperature calibration method is relatively simple and can better achieve real-time calibration for sensor application scenarios. Finally, to verify the effectiveness of the proposed method, numerous laboratory experiments were implemented. The temperature drift was reduced from about 700 nT before calibration to about 1 nT, root mean square error RMSE=11.7189, indicating that the proposed method has a good temperature calibration effect on the data measured by the fluxgate sensor within the variable temperature background. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Curve Fitting Fluxgate Sensor Temperature Calibration

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Nanoscaffold Ba_0.6Sr_0.4TiO₃:Nd₂O₃ ferroelectric memristors crossbar array for neuromorphic computing and secure encryption

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Journal of Materiomics 2025年第5期11卷

作者： Zhang, Weifeng Xu, Jikang Wang, Yongrui Zhang, Yinxing Wang, Yu Li, Pengfei Jia, Yongqing Zhao, Zhen Li, Changliang Yang, Biao Hou, Yue Guo, Zhenqiang Huang, Zeze Qi, Yincheng Yan, Xiaobing Institute of Life Science and Green Development Key Laboratory of Brain-like Neuromorphic Devices and Systems of Hebei Province College of Electronic and Information Engineering Hebei Baoding 071002 China Hebei Key Lab of Optic-Electronic Information and Materials College of Physics Science & Technology Hebei Baoding 071002 China Department of Electronic and Communication Engineering Intelligent Vision Computing Research Institute North China Electric Power University Hebei Baoding 071003 China

Recent advancements in AI have spurred interest in ferroelectric memristors for neuromorphic chips due to their ability to precisely control resistive states through polarization flip-flop without electroforming. However, oxygen vacancies in these devices often cause high leakage current, low endurance, and dispersed switching voltages. Here, we introduce a silicon-based integrated (Ba_0.6Sr_0.4TiO₃)_0.5(Nd₂O₃)_0.5 (BSTN) nanoscaffolded ferroelectric thin film memristor with a vertically self-assembled nanocomposite structure (VSNs) optimally oriented on La_0.67Sr_0.33MnO₃/SrTiO₃/P[sbnd]Si substrates. This device demonstrates a widely tunable ferroelectric domain range (0°–180°), high remnant polarization (21.04 μC/cm²), and a greater number of unitary states (16 states or 4 bits). It exhibits high durability, enduring over 10⁹ switching cycles. The switching mechanism combines ferroelectric polarization and oxygen vacancy migration, enabling the simulation of biological synaptic functions via bi-directional conductance tunability. Additionally, we implemented a low-power (0.57 pJ per event) multi-factor secure encryption system for smart locks using 16×16 BSTN memristor crossbar arrays and a pressure sensor. Under multiple factors (disordered inputs, specific users, and corresponding passwords) the system recognized passwords with 97.6% accuracy and a 3.8% loss rate after 500 iterations. Overall, this work establishes a robust foundation for advancing multilevel storage, neuromorphic computing, and AI chip applications based on ferroelectric memristors. © 2025 The Authors

关键词： Ferroelectric memristor Interface channel Multi-factor secure encryption system Nanoscaffolded

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The Combination of Two Control Strategies for Series Hybrid Electric Vehicles

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IEEE/CAA Journal of Automatica Sinica 2019年第2期6卷 596-608页

作者： Can Luo Zhen Shen Simos Evangelou Gang Xiong Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Cloud Computing Center Chinese Academy of Sciences IEEE Department of Electrical and Electronic Engineering Imperial College London Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Qingdao Academy of Intelligent Industries

With most countries paying attention to the environment protection, hybrid electric vehicles have become a focus of automobile research and development due to the characteristics of energy saving and low emission. Power follower control strategy(PFCS) and DC-link voltage control strategy are two sorts of control strategies for series hybrid electric vehicles(HEVs). Combining those two control strategies is a new idea for control strategy of series hybrid electric vehicles. By tuning essential parameters which are the defined constants under DClink voltage control and under PFCS, the points of minimum mass of equivalent fuel consumption(EFC) corresponding to a series of variables are marked for worldwide harmonized light vehicles test procedure(WLTP). The fuel economy of series HEVs with the combination control schemes performs better compared with individual control scheme. The results show the effects of the combination control schemes for series HEVs driving in an urban environment.

关键词： DC-Link voltage control power follower control strategy series hybrid electric vehicles tuning

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TLSTMF-YOLO: Transfer Learning and Feature Fusion Network for Earthquake-Induced Landslide Detection in Remote Sensing Images

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Meng, Shaoqiang Shi, Zhenming Pirasteh, Saied Liberata Ullo, Silvia Peng, Ming Zhou, Changshi Nunes Goncalves, Wesley Zhang, Limin Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Key Laboratory of Geotechnical and Underground Engineering Ministry of Education Shanghai200092 China Institute of Artificial Intelligence Shaoxing University Zhejiang Shaoxing312000 China Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Geotechnics and Geomatics Tamil Nadu Chennai600 077 India University of Sannio Department of Engineering Benevento82100 Italy Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Shanghai200092 China Federal University of Mato Grosso do Sul Faculty of Computing Campo Grande79070-900 Brazil The Hong Kong University of Science and Technology Department of Civil and Environmental Engineering Hong Kong Hong Kong

Detecting earthquake-induced landslides in remote sensing images is challenging due to the varying sizes of landslides, uneven distribution, and the prevalence of small targets. This study proposes a novel approach, the TLSTMF-YOLO model, which combines a C3-Swin-Transformer and multiscale feature fusion techniques to enhance detection accuracy and efficiency. key innovations include the use of a convolutional block attention module (CBAM) to improve feature representation, and a bidirectional feature pyramid network (BiFPN) for optimized cross-scale feature fusion. To address data scarcity, a transfer learning strategy is applied, supported by an AdamW optimizer and cosine learning rate strategy for faster convergence. Evaluations on the Jiuzhaigou and Luding landslide datasets demonstrate the model's effectiveness, achieving precision, recall, and mean average precision (mAP)@0.5 of 95.7%, 89.9%, and 90.5% on the Jiuzhaigou dataset, and 96.0%, 90.9%, and 94.5% on the Luding dataset, respectively. In addition, the model processes frames efficiently, with times of 6.61 and 12.2 ms on the two datasets. These results confirm the model's capability for accurate and efficient landslide detection, highlighting its potential for real-world applications. © 1980-2012 IEEE.

关键词： Earthquakes

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Exact first passage time distribution for nonlinear chemical reaction networks II: monomolecular reactions and a A + B → C type of second-order reaction with arbitrary initial conditions

arXiv

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arXiv 2025年

作者： Rao, Changqian Waxman, David Lin, Wei Song, Zhuoyi School of Mathematical Sciences Fudan University Shanghai200433 China Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai200433 China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence [Fudan University Ministry of Education China MOE Frontiers Center for Brain Science Fudan University Shanghai200433 China Zhangjiang Fudan International Innovation Center Shanghai China

In biochemical reaction networks, the first passage time (FPT) of a reaction quantifies the time it takes for the reaction to first occur, from the initial state. While the mean FPT historically served as a summary metric, a far more comprehensive characterization of the dynamics of the network is contained within the complete FPT distribution. The relatively uncommon theoretical treatments of the FPT distribution that have been given in the past have been confined to linear systems, with zero and first-order processes. Recently, we presented theoretically exact solutions for the FPT distribution, within nonlinear systems involving two-particle collisions, such as A+B → C. Although this research yielded invaluable results, it was based upon the assumption of initial conditions in the form of a Poisson distribution. This somewhat restricts its relevance to real-world biochemical systems, which frequently display intricate behaviour and initial conditions that are non-Poisson in nature. Our current study extends prior analyses to accommodate arbitrary initial conditions, thereby expanding the applicability of our theoretical framework and providing a more adaptable tool for capturing the dynamics of biochemical reaction networks. © 2025, CC BY.

关键词： Poisson distribution

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Parallel implementation of w-projection wide-field imaging

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Science Bulletin 2019年第9期64卷 586-594页

作者： Baoqiang Lao Tao An Ang Yu Wenhui Zhang Junyi Wang Quan Guo Shaoguang Guo Xiaocong Wu Shanghai Astronomical Observatory Key Laboratory of Radio AstronomyChinese Academy of Sciences Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology

w-Projection is a wide-field imaging technique that is widely used in radio synthesis arrays. Processing the wide-field big data generated by the future Square Kilometre Array(SKA) will require significant updates to current methods to significantly reduce the time consumed on data processing. Data loading and gridding are found to be two major time-consuming tasks in w-projection. In this paper, we investigate two parallel methods of accelerating w-projection processing on multiple nodes: the hybrid Message Passing Interface(MPI) and Open Multi-Processing(OpenMP) method based on multicore Central Processing Units(CPUs) and the hybrid MPI and Compute Unified Device Architecture(CUDA)method based on Graphics Processing Units(GPUs). Both methods are successfully employed and operated in various computational environments, confirming their robustness. The experimental results show that the total runtime of both MPI + OpenMP and MPI + CUDA methods is significantly shorter than that of single-thread processing. MPI + CUDA generally shows faster performance when running on multiple nodes than MPI + OpenMP, especially on large numbers of nodes. The single-precision GPU-based processing yields faster computation than the double-precision processing; while the single-and doubleprecision CPU-based processing shows consistent computational performance. The gridding time remarkably increases when the support size of the convolution kernel is larger than 8 and the image size is larger than 2,048 pixels. The present research offers useful guidance for developing SKA imaging pipelines.

关键词： Radio synthesis arrays Square kilometre array Wide field imaging Parallelization w-Projection

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Optimizing top-k retrieval:submodularity analysis and search strategies

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Frontiers of Computer Science 2016年第3期10卷 477-487页

作者： Chaofeng SHA Keqiang WANG Dell ZHANG Xiaoling WANG Aoying ZHOU School of Computer Science Shanghai Key Laboratory of Intelligent Information ProcessingFudan University Shanghai Key Laboratory of Trustworthy Computing East China Normal University Department of Computer Science and Information Systems BirkbeckUniversity of London

The key issue in top-fc retrieval,finding a set of fc documents(from a large document collection) that can best answer a user's query,is to strike the optimal balance between relevance and *** this paper,we study the top-fc retrieval problem in the framework of facility location analysis and prove the submodularity of that objective function which provides a theoretical approximation guarantee of factor 1--for the(best-first) greedy search ***,we propose a two-stage hybrid search strategy which first obtains a high-quality initial set of top-fc documents via greedy search,and then refines that result set iteratively via local *** on two large TREC benchmark datasets show that our two-stage hybrid search strategy approach can supersede the existing ones effectively and efficiently.

关键词： top-k retrieval diversification submodular function maximization

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