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第41届中国控制会议

作者： Guan Wang Yufeng Zhan Yuanqing Xia Liping Yan Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology School of Information Science and Engineering University of ZaoZhuang

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the rapid development of cloud computing and control theory,a new paradigm of networked control systems named cloud control systems has been proposed to satisfy the requirements of large-scale and complex *** is critical to manage large-scale tasks with personalized needs on the large number of heterogeneous ***,current TCP/IPbased addressing approach does not consider the runtime constraints of tasks,resulting highly concurrent service search,and communication between tasks will become the system *** this paper,we propose a task property encoding method which takes multi-dimensional properties into *** on the proposed encoding method,we design a uniform addressing method for tasks in the ***,we experimentally demonstrate the effectiveness of task property encoding,and the unified addressing method for tasks is more effective than other methods in the case of high task concurrency.

关键词： Cloud control systems address encoding cloud-edge-device cooperation

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Port and Radiation Pattern Decoupled Microstrip Antennas Using Shorting Vias

Port and Radiation Pattern Decoupled Microstrip Antennas Usi...

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2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023

作者： Liu, Guang Yao Yang, Nan Leung, Kwok Wa City University of Hong Kong State Key Laboratory of Terahertz and Millimeter Waves Department of Electrical Engineering Kowloon Hong Kong CityU Shenzhen Research Institute Information and Communication Technology Centre Shenzhen518057 China Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Guangzhou510006 China

ISBN: (纸本)9798350358971

In this paper, a microstrip antenna array using shorting vias is presented with port and radiation pattern decoupling. Shorting vias on the passive patch introduce an opposite current component, canceling the original coupling currents and obtaining the decoupling of antenna elements. To verify the decoupling method, a sample is designed at 3.6 GHz. The measured port isolation of the decoupled antenna array is more than 25.7 dB. It should be highlighted that the radiation patterns of decoupled antenna elements are all along the broadside direction, defined as the radiation pattern decoupling effect. © 2023 IEEE.

关键词： Antenna decoupling microstrip antenna (MA) mutual coupling radiation pattern decoupling

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Beyond Boundaries: Learning a Universal Entity Taxonomy across Datasets and Languages for Open Named Entity Recognition 31

Beyond Boundaries: Learning a Universal Entity Taxonomy acro...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Yang, Yuming Zhao, Wantong Huang, Caishuang Ye, Junjie Wang, Xiao Zheng, Huiyuan Nan, Yang Wang, Yuran Xu, Xueying Huang, Kaixin Zhang, Yunke Gui, Tao Zhang, Qi Huang, Xuanjing School of Computer Science Fudan University China Honor Device Co. Ltd. Institute of Modern Languages and Linguistics Fudan University China Pengcheng Laboratory China Research Institute of Intelligent Complex Systems Fudan University China Shanghai Key Laboratory of Intelligent Information Processing China

ISBN: (纸本)9798891761964

Open Named Entity Recognition (NER), which involves identifying arbitrary types of entities from arbitrary domains, remains challenging for Large Language Models (LLMs). Recent studies suggest that fine-tuning LLMs on extensive NER data can boost their performance. However, training directly on existing datasets neglects their inconsistent entity definitions and redundant data, limiting LLMs to dataset-specific learning and hindering out-of-domain adaptation. To address this, we present B2NERD, a compact dataset designed to guide LLMs' generalization in Open NER under a universal entity taxonomy. B2NERD is refined from 54 existing English and Chinese datasets using a two-step process. First, we detect inconsistent entity definitions across datasets and clarify them by distinguishable label names to construct a universal taxonomy of 400+ entity types. Second, we address redundancy using a data pruning strategy that selects fewer samples with greater category and semantic diversity. Comprehensive evaluation shows that B2NERD significantly enhances LLMs' Open NER capabilities. Our B2NER models, trained on B2NERD, outperform GPT-4 by 6.8-12.0 F1 points and surpass previous methods in 3 out-of-domain benchmarks across 15 datasets and 6 languages. The data, models, and code are publicly available at https://***/UmeanNever/B2NER. © 2025 Association for Computational Linguistics.

关键词： Taxonomies

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IVR-SSM: Industrial Vehicular Robot Safe & Smart Move Using Wheel-Encoder and Inertial-RGB-Depth Measurements 30

IVR-SSM: Industrial Vehicular Robot Safe & Smart Move Using ...

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30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

作者： Liu, Yuanhao Liang, Wei Wang, Chu Zhang, Xin Gao, Huanbing Zhang, Yinlong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China School of Information and Electrical Engineering Shandong Jianzhu University Jinan China Shandong Key Laboratory of Intelligent Buildings Technology Jinan China

ISBN: (纸本)9798350391916

Safe & smart move (SSM) aims to help industrial vehicular robot (IVR), such as warehousing robots, running safely and smartly by detecting the obstacles in front and maintaining a safe distance & attitude. However, the traditional SSM methods suffer the drawbacks of limited ranges, inaccurate regression of safety distance & orientation between the robot and the forward unexpected obstacles, and the inappropriate IVR control strategies. To solve these issues, this paper designs an innovative real-time safety-aware framework using the complementary Wheel-Encoder and Inertial-RGB-Depth measurements to ensure the IVR running safely, reasonably and reliably. To estimate the robot running states, we take advantages of the complementary wheel encoder, monocular RGB images and inertial measurements to obtain the robot positions, orientations, angular and linear velocities in a tightly-coupled manner. To improve the safety relative distance & attitude estimation accuracy, we exploit the RGB and depth measurements in a task-oriented fashion. The forward obstacles with the specific contours are detected using the Mask-RCNN model, followed by the Gaussian Mixture Model to obtain the forward obstacle depth. Eventually, an IVR control strategy is designed to maintain the robot safety distance and orientation, and to keep the minimum damage to the robot mechanical system. The presented method has been evaluated on the developed industrial vehicular robot safety perception platform. The experimental results prove the competitiveness against the state-of-the-art methods. © 2024 IEEE.

关键词： Industrial robots

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Toward Cable-Driven Continuum Robots: Micro-Motion Augmentation Using Eccentrically Arranged Fibres with Eccentric Lumens

Toward Cable-Driven Continuum Robots: Micro-Motion Augmentat...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Lin, Zecai Zhou, Cheng Zou, Yun Gao, Anzhu Shanghai Jiao Tong University Institute of Medical Robotics Department of Automation China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781665481090

Micro-motion augmentation of macro-motion continuum robot can largely enhance its micro-operation capability during surgery. However, most existing micro-motion continuum robots have non-compact mechanical structure or non-smooth micro tip motion, which leads to complicated control in micro lumens. This paper proposes a micro-motion augmentation method by rotating eccentrically arranged fibres with eccentric lumens for cable-driven continuum robots. Two thermal drawn polymer fibres with an eccentric lumen on each are inserted into its eccentric lumens of the continuum robot. The micro-motion mechanism relies on small changes in the neutral axis of the continuum robot due to the rotation of the eccentrically arranged fibres. A kinematic model considering variable neural axis is built to describe the micro motion, and a simulation is conducted to investigate the deformation characteristics. The resolution and micro motion with respect to different structural parameters are also analysed. Detailed experiments are performed to validate the effectiveness of the proposed method, and results indicate that the repeatability of micro-motion is 10.1 μm (4.0 %). © 2024 IEEE.

关键词： Robotic surgery

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Fog Images Generation About Unmanned Surface Vessels with Improved Generative Adversarial Network 42

Fog Images Generation About Unmanned Surface Vessels with Im...

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42nd Chinese control Conference, CCC 2023

作者： Tang, Yifeng Huang, Zhihui Tang, Chuancong Luo, Chuanshang Xu, Yifan Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control Wuhan430074 China The State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

This paper proposes a fog weather data augmentation method for the unmanned surface vessels (USVs) via improved Generative Adversarial Network(GAN) model. First, a generator scheme for GAN is proposed with the guided generation of the atmospheric scattering model in this paper. A Laplacian Pyramid Based Depth Residuals model is added to the generator which reduces the difficulty of generating fog images caused by the degradation of water surface image and improves the quality of generated images. Finally, fog images are generated from sunny weather images collected with HUST-12C by LPBDR-GAN model and experiments show that generated images are very close to real fog images. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Generative adversarial networks

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controllability Analysis and Stable control for Planar Non-One Passive Joint Underactuated Robot with Bi-Directional Approach 42

Controllability Analysis and Stable Control for Planar Non-O...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Zixin Wei, Ziang Wang, Wei Gong, Xiangyu Zeng, Ba Wang, Lejun School of Electrical and Information Engineering Wuhan Institute of Technology China Wuhan Textile University Hubei Key Laboratory of Digital Textile Equipment China Chongqing University of Posts and Telecommunications Chongqing Key Laboratory of Complex Systems and Bionic Control China

ISBN: (纸本)9789887581543

In this paper, we consider the controllability and stability control problem for planar underactuated robots with non-one passive joints. The dynamic constraints of the robot are mainly caused by nonholonomic constraints. Firstly, we establish the dynamic model of this system and analyze its controllability. Then, based on location and number of passive joints, we divide the system into different configurations. Next, we propose a stable control method based on bi-directional approach to achieve the stable control of different systems. At last, the numerical simulation conclusion illuminate the feasibility of this method. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： controllability

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Segmentation of CAD models using hybrid representation

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虚拟现实与智能硬件(中英文) 2025年第2期7卷 188-202页

作者： Claude UWIMANA Shengdi ZHOU Limei YANG Zhuqing LI Norbelt MUTAGISHA Edouard NIYONGABO Bin ZHOU State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Peace-Bay Academy of Virtual Reality Shenyang 110004China China Aerospace Systems Engineering Corporation Beijing 100070China Department of Signal and Information Processing Beihang UniversityBeijing 100191China Department of Computer Science University of SherbrookeSherbrooke J1C0A1Canada

In this paper,we introduce an innovative method for computer-aided design(CAD)segmentation by concatenating meshes and CAD *** previous CAD segmentation methods have achieved impressive performance using single representations,such as meshes,CAD,and point ***,existing methods cannot effectively combine different three-dimensional model types for the direct conversion,alignment,and integrity maintenance of geometric and topological ***,we propose an integration approach that combines the geometric accuracy of CAD data with the flexibility of mesh representations,as well as introduce a unique hybrid representation that combines CAD and mesh models to enhance segmentation *** combine these two model types,our hybrid system utilizes advanced-neural-network techniques to convert CAD models into mesh *** complex CAD models,model segmentation is crucial for model retrieval and *** partial retrieval,it aims to segment a complex CAD model into several simple *** first component of our hybrid system involves advanced mesh-labeling algorithms that harness the digitization of CAD properties to mesh *** second component integrates labelled face features for CAD segmentation by leveraging the abundant multisemantic information embedded in CAD *** combination of mesh and CAD not only refines the accuracy of boundary delineation but also provides a comprehensive understanding of the underlying object *** study uses the Fusion 360 Gallery *** results indicate that our hybrid method can segment these models with higher accuracy than other methods that use single representations.

关键词： B-RepNet hybrid segmentation CAD models classification MeshCNN MeshCAD-Net

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Multi-Channel Based on Attention Network for Infrared Small Target Detection

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 414-427页

作者：张彦军王碧云蔡云泽 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Institute of Aerospace Control Technology Shanghai 201109China Infrared Detection Technology R&D Center of China Aerospace Science and Technology Corporation Shanghai 201109China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghai 200240China

Infrared detection technology has the advantages of all-weather detection and good concealment,which is widely used in long-distance target detection and tracking ***,the complex background,the strong noise,and the characteristics of small scale and weak intensity of targets bring great difficulties to the detection of infrared small targets.A multi-channel based on attention network is proposed in this paper,aimed at the problem of high missed detection rate and false alarm rate of traditional algorithms and the problem of large model,high complexity and poor detection performance of deep learning ***,given the difficulty in extracting the features of infrared multiscale and small dim targets,the multiple channels are designed based on dilated convolution to capture multiscale target ***,the coordinate attention block is incorporated in each channel to suppress background clutters adaptively and enhance target *** addition,the fusion of shallow detail features and deep abstract semantic features is realized by synthesizing the contextual attention fusion ***,it is verified that,compared with other state-of-the-art methods based on the datasets SIRST and MDFA,the proposed algorithm further improves the detection effect,and the model size and computational complexity are smaller.

关键词： infrared image small target detection deep learning attention mechanism feature fusion

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Building Temperature and Humidity Adaptive control for a Multi-Zone HVAC System Using Hybrid Modeling Method

Building Temperature and Humidity Adaptive Control for a Mul...

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2022 IEEE International Conference on Industrial Technology, ICIT 2022

作者： Jiang, Yuliang Zhu, Shanying Xu, Qimin Yang, Bo Guan, Xinping Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China 200240 Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China 200240

ISBN: (纸本)9781728119489

In this paper, the heating, ventilation and air conditioning (HVAC) system as the contributor of building climate management is studied on multi-zone climate dynamics modelling and control for occupancy comfort. The first-principles model together with data-driven model as the hybrid model is proposed for comprehensive multi-zone hygro-thermal dynamics. The unmodeled climate dynamics such as unknown nonlinearity and uncertainty is modeled in a linear form based on the compact form dynamic linearization (CFDL) method. Then model free adaptive control (MFAC) scheme including controller design and parameter estimation is proposed to realize multi-zone climate control and occupancy comfort. The dynamic response performance of the hybrid model-based adaptive control and the first-principles model-based adaptive control has been tested in a multi-zone building with four different zones. The results show that the proposed hybrid model-based adaptive control scheme can achieve obvious performance improvement in minimizing steady-state error. © 2022 IEEE.

关键词： controllers

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