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检索条件"机构=Laboratory of Intelligent Control and Optimization of Complex Systems"
2421 条 记 录,以下是61-70 订阅
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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 lear... 详细信息
来源: 评论
A Task Assignment Scheme Designed for Online Urban Sensing Based on Sparse Mobile Crowdsensing
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IEEE Internet of Things Journal 2025年
作者: Zeng, Hongjian Xiong, Yonghua She, Jinhua Yu, Anjun China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China Tokyo University of Technology School of Engineering Hachioji Tokyo192-0982 Japan Jiangxi Ganyue Expressway Co. Ltd Jiangxi Nanchang330000 China
Sparse Mobile Crowdsensing (SMCS) achieves urban-scale environmental sensing by assigning tasks to workers in specific subareas and inferring global data from the collected information. However, the effectiveness of S... 详细信息
来源: 评论
Multimodal Emotion Recognition Based on Multi-Scale Facial Features and Cross-Modal Attention  26
Multimodal Emotion Recognition Based on Multi-Scale Facial F...
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26th International Conference on Industrial Technology, ICIT 2025
作者: Bao, Chengao Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru School of Automation China University of Geosciences Wuhan430074 China School of Automation Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2G7 Canada Tokyo Institute of Technology Yokohama226-8502 Japan Tokyo Institute of Technology Tokyo226-8502 Japan
A multi-modal emotion recognition method based on facial multi-scale features and cross-modal attention (MS-FCA) network is proposed. The MSFCA model improves the traditional single-branch ViT network into a two-branc... 详细信息
来源: 评论
Optimal fusion estimation for stochastic systems with cross-correlated sensor noises
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Science China(Information Sciences) 2017年 第12期60卷 57-70页
作者: Liping YAN Yuanqing XIA Mengyin FU School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology
This paper is concerned with the optimal fusion of sensors with cross-correlated sensor *** taking linear transformations to the measurements and the related parameters, new measurement models are established, where t... 详细信息
来源: 评论
Adaptive unscented Kalman filter for parameter and state estimation of nonlinear high-speed objects
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Journal of systems Engineering and Electronics 2013年 第4期24卷 655-665页
作者: Fang Deng Jie Chen Chen Chen School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems
An adaptive unscented Kalman filter (AUKF) and an augmented state method are employed to estimate the timevarying parameters and states of a kind of nonlinear high-speed objects. A strong tracking filter is employed... 详细信息
来源: 评论
Adaptive Robust Dead-Zone Compensation control of Electro-Hydraulic Servo systems with Load Disturbance Rejection
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Journal of systems Science & complexity 2015年 第2期28卷 341-359页
作者: HE Yudong WANG Junzheng HAO Renjian Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology
A backstepping method based adaptive robust dead-zone compensation controller is pro- posed for the electro-hydraulic servo systems (EHSSs) with unknown dead-zone and uncertain system parameters. Variable load is se... 详细信息
来源: 评论
Utilizing semantically enhanced self-supervised graph convolution and multi-head attention fusion for herb recommendation
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Artificial Intelligence in Medicine 2025年 164卷 103112-103112页
作者: Tang, Xianlun Tang, Yuze Liu, Xinran Zhang, Haochuan Dang, Xiaoyuan Wang, Ying Xu, Zihui Chongqing Key Laboratory of Complex Systems and Autonomous Control Chongqing University of Posts and Telecommunications Chongqing400065 China School of Intelligent Engineering Chongqing College of Mobile Communication Chongqing401520 China Big Data and Internet of Things School Chongqing Vocational Institute of Engineering Chongqing402260 China Xinqiao Hospital Army Medical University Chongqing400037 China
Traditional Chinese herbal medicine has long been recognized as an effective natural therapy. Recently, the development of recommendation systems for herbs has garnered widespread academic attention, as these systems ... 详细信息
来源: 评论
The Separate Meter in Separate Meter Out control System Using Dual Servo Valves Based on Indirect Adaptive Robust Dynamic Surface control
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Journal of systems Science & complexity 2019年 第2期32卷 557-576页
作者: CHEN Guangrong WANG Junzheng WANG Shoukun ZHAO Jiangbo SHEN Wei The Key Laboratory of Drive and Control of Servo Motion Systems Beijing Institute of Technology The Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology
Due to the demand for energy efficiency in electro-hydraulic systems, the separate meter in and separate meter out(SMISMO) control system attracts vast attention. In this paper, the SMISMO control system was configure... 详细信息
来源: 评论
Cooperative Hierarchical Coverage control of Multi-Agent systems with Non-holonomic Constraints in Poriferous Environments
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IEEE Transactions on control of Network systems 2025年
作者: Zou, Jiayu Zhang, Hai-Tao Zhai, Chao Xing, Ning Ma, Yong Liu, Xingjian Huazhong University of Science and Technology School of Artificial Intelligence and Automation The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China China University of Geosciences School of Automation China The MOE Engineering Research Center of Intelligent Technology for Geo-Exploration Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Academician Workstation of China COSCO Shipping Corporation Ltd. Shanghai200120 China Wuhan University of Technology Sanya Science and Education Innovation Park Sanya572000 China Wuhan University of Technology Chongqing Research Institute Chongqing401120 China
It has long posed a challenging task to optimally deploy multi-agent systems (MASs) to cooperatively coverage poriferous environments in real cooperative detection applications. In response to this challenge, this pap... 详细信息
来源: 评论
Multimodal Image Matching based on Frequency-domain Information of Local Energy Response
arXiv
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arXiv 2025年
作者: Yang, Meng Chen, Jun Gong, Wenping Wei, Longsheng Tian, Xin 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 China University of Geosciences Wuhan430074 China Electronic Information School Wuhan University Wuhan430072 China
Complicated nonlinear intensity differences, nonlinear local geometric distortions, noises and rotation transformation are main challenges in multimodal image matching. In order to solve these problems, we propose a m... 详细信息
来源: 评论