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第33届中国控制与决策会议

作者： Xiaofei Zhang Hongbin Ma Junyong Chen Weixue Li School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Adaptive dynamic programming(ADP) is a kind of intelligent control method,and it is a non-model-based method that can directly approximate the optimal control policy via online *** gradient algorithm is usually used to update weights of action networks and critic networks,however it is clear that gradient descent-based learning methods are generally very slow due to improper learning steps or may easily converge to local *** this paper,in order to overcome those disadvantages of gradient descent-based learning methods,a novel ADP algorithm based on initial-training-free online extreme learning machine(ITF-OELM),in which the critic network link weights of hidden nodes to output nodes can be obtained by least squares instead of gradient algorithm,is ***,the ADP algorithm based on ITF-OELM is tested on a discrete time torsional pendulum system,and simulation results indicate that this algorithm makes the system converge in a shorter time compared with the ADP based on gradient algorithm.

关键词： Adaptive Dynamic Programming Extreme Learning Machine Discrete-time systems

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A Review of Recent Advances in Coordination Between Unmanned Aerial and Ground Vehicles

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无人系统（英文） 2021年第2期9卷 97-117页

作者： Yulong Ding Bin Xin Jie Chen School of Automation Beijing Institute of TechnologyBeijing 100081P.R.China Peng Cheng Laboratory Shenzhen 518055P.R.China School of Automation Beijing Institute of TechnologyBeijing 100081P.R.China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of TechnologyBeijing 100081P.R.China

Coordination between unmanned aerial vehicles(UAVs)and unmanned ground vehicles(UGVs)has received increasing attention in recent *** list of successful applications of UAV-UGV coordination systems is growing and demonstrates that UAV-UGV coordination can provide real-world solutions that other types of coordination cannot *** paper systematically reviews the advances in UAV-UGV coordination systems during the period of 2015-2020 and offers a comprehensive investigation and analysis of the recent ***,the essential elements in the UAV-UGV coordination systems are analyzed,and four key functional roles are *** close collaboration among functional roles can achieve the UAV-UGV coordination on perception,task,and *** the perspective of functional roles,UAV-UGV coordination systems can be further classified into eight *** functional-role-based category pro-vides novel insights into analyzing various patterns of UAV-UGV *** paper also discusses the challenges related to UAV-UGV coordination.

关键词： UAV-UGV coordination systems air-ground collaboration unmanned aerial vehicle unmanned ground vehicle

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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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Design and locomotion characteristic analysis of a novel tensegrity hopping robot*

Design and locomotion characteristic analysis of a novel ten...

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IEEE International Conference on Robotics and Biomimetics

作者： Jixue Mo Changqing Gao Hao Fang Qingkai Yang Department of Strategic and Advanced Interdisciplinary Research Peng Cheng Laboratory Shenzhen China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

In consideration of the poor locomotion ability of most traditional tensegrity robot, a novel tensegrity hopping robot powered by push-pull electromagnets was proposed with better locomotivity. It is able to conduct stable consecutive progressing action and turning action through hopping. This paper covers the structural design, theoretical modeling of the robot’s hopping process, as well as its self-righting analysis, simulation and experimental verification. The average moving speed and relative moving speed were measured to be 0.334m/s and 0.641 body length/s respectively, which obviously surpass the general moving ability of most traditional tensegrity robot. In addition, the robot was also validated to have good self-righting characteristic for stable consecutive hopping. Thus this robot can be potentially applied for search, rescue, detection, etc. in outdoor and unstructured environment.

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A Real-Time Visual-Inertial Monocular Odometry by Fusing Point and Line Features

A Real-Time Visual-Inertial Monocular Odometry by Fusing Poi...

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第40届中国控制会议

作者： Chengwei Li Liping Yan Yuanqing Xia Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

In this paper, a monocular visual-inertial odometry that utilize both point and line features is deduced. Compared with point features, line features provide more geometric information of the environment, which are more reliable in textureless scenes. However, extracting line segment features from the image are very time consuming, which will affect the real-time performance of the system. To deal with this problem, EDLines line segment detector is introduced to replace the LSD *** properties of lines are utilized to reject the mismatching of line segment feature. Pl ¨ucker coordinates and orthonormal representation of lines are used to represent 3 D lines. Afterwards, we optimize the state by minimizing a cost function consists of pre-integrated IMU residuals and visual feature re-projection residuals in a sliding window optimization framework. The proposed odometry was tested on the public datasets. The results demonstrate that the presented system can operate in real time with high accuracy.

关键词： visual-inertial odometry(VIO) point and line feature visual simultaneous localization and mapping(SLAM)

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Data-Driven Learning and control with Event-Triggered Measurements

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IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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Information Fusion of Topological Structure and Node Features in Graph Neural Network

Information Fusion of Topological Structure and Node Feature...

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第40届中国控制会议

作者： Hongwei Zhang Can Wang Yuanqing Xia Tijin Yan Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

Graph neural networks(GNNs) have shown great popularity and achieved promising performance on various graph-based tasks in the past years. However, there is little work that explores the information fusion mechanism, which plays an import role in GNNs. Besides, datasets in the real world often have noises, which make the information fusion difficult. In this paper, we give an information-theoretic explanation. Specifically, we focus on how the information from topological structures and node features fuses and how different information contributes to the downstream task. Furthermore, we propose a general framework named M-GCN to express the fusion process in GNNs. Graph embeddings and feature graph are introduced to extract the information from topological structure and node features separately in M-GCN. Extensive experiments are conducted on several benchmark datasets and experimental results show that our proposed models are more robust and outperform state-of-the-art methods.

关键词： Information Fusion Graph Neural Network Graph embedding

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Smooth quadrotor trajectory generation for tracking a moving target in cluttered environments

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Science China(Information Sciences) 2021年第7期64卷 132-147页

作者： Lele XI Zhihong PENG Lei JIAO Ben M.CHEN School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Peng Cheng Laboratory Department of Mechanical and Automation Engineering The Chinese University of Hong Kong

In this paper, we present a trajectory generation method of a quadrotor, based on the optimal smoothing B-spline, for tracking a moving target with consideration of relative tracking pattern or limited field of view of the onboard sensor in cluttered environments. Compared to existing methods, safe flying zone,vehicle physical limits, and smoothness are fully considered to guarantee flight safety, kinodynamic feasibility, and tracking performance. To tackle the cluttered environments, a parallel particle swarm optimization algorithm is applied to find the feasible waypoints that the generated trajectory should be as close to as possible, with consideration of the target's future state as well as obstacles to trade off the tracking performance and flight safety. Then, a sequential motion planning method, considering the above constraints, is applied and embedded into a cost function for solving the problem of robust tracking trajectory generation for the quadrotor via a convex optimization approach. The feasibility and effectiveness of the proposed method are verified by numerical simulations.

关键词： quadrotor target tracking trajectory generation B-spline convex optimization

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Autonomous Tracking control for Four-Wheel Independent Steering Robot Based on Improved Pure Pursuit

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Journal of Beijing Institute of Technology 2020年第4期29卷 466-473页

作者： Jing Li Qingbin Wu Junzheng Wang Hui Qin Jiehao Li Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information TechnologySchool of AutomationBeijing Institute of TechnologyBeijing 100081China

Autonomous tracking control is one of the fundamental challenges in the field of robotic autonomous navigation,especially for future intelligent *** this paper,an improved pure pursuit control method is proposed for the path tracking control problem of a four-wheel independent steering *** on the analysis of the four-wheel independent steering model,the kinematic model and the steering geometry model of the robot are *** the path tracking control is realized by considering the correlation between the look-ahead distance and the velocity,as well as the lateral error between the robot and the reference *** experimental results demonstrate that the improved pure pursuit control method has the advantages of small steady-state error,fast response and strong robustness,which can effectively improve the accuracy of path tracking.

关键词： autonomous tracking control four-wheel independent steering robot pure pursuit lateral error

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Isochronous Temporal Metric for Neighbourhood Analysis in Classification Tasks

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SN Computer Science 2023年第6期4卷 1-12页

作者： Kumar, Amit Krishan Mai, Nguyễn Ngọc Tian, Ke Xia, Yuanqing Institute of Research and Development Duy Tan University Da Nang Vietnam Faculty of Electrical-Electronic Engineering Duy Tan University Da Nang Vietnam Faculty of Chinese Language School of Foreign Language Duy Tan University Da Nang Vietnam State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China

Machine learning, classification, and clustering techniques use the distance functions to evaluate the proximity between data entries and deduce the best neighbouring element and the closest matching entry. The best neighbour is not only the closest neighbour but a neighbour that is quick to respond. In view of that, a time-based isochronous metric is introduced to evaluate the best neighbours and form linkages by grouping similar entities. The proposed method uses parametric equations of the fastest descent and solves the time variables for attributes localised in curved space–time. The time metric is compared with commonly used distance metrics for accuracy in classification and clustering using benchmark and commonly used datasets. The nearest-neighbour technique is used for evaluating classification accuracy, and an adjusted random index (ARI) is used to evaluate clustering. The proposed method shows better accuracy and ARI in comparison to distance functions. It also assigns better weights to attributes of the dataset and easily identifies repeated patterns in noisy time series data.

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