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Automatic Robotic Cranium-Milling: A Motion Control Study of In Vitro Animal Experiments 期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2024, 页码: 1-14
作者:  Bian GB(边桂彬);  Qian C(钱琛);  Li Z(李桢);  Ye Q(叶强);  Ge PC(葛培聪);  Zhao JZ(赵继宗)
Adobe PDF(2827Kb)  |  收藏  |  浏览/下载：30/8  |  提交时间：2024/05/28
Hedonic Coalition Formation for Distributed Task Allocation in Heterogeneous Multi-agent System 期刊论文
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2024, 页码: 13
作者:  Wang, Lexing;  Qiu, Tenghai;  Pu, Zhiqiang;  Yi, Jianqiang;  Zhu, Jinying;  Yuan, Wanmai
Adobe PDF(2578Kb)  |  收藏  |  浏览/下载：96/8  |  提交时间：2024/03/13
Coalition formation  hedonic games  heterogeneous agents  Nash stable  task allocation  
Robotic Automatic Drilling for Craniotomy: Algorithms and In Vitro Animal Experiments 期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2023, 页码: 12
作者:  Bian, Gui-Bin;  Wei, Bing-Ting;  Li, Zhen;  Ge, Peicong;  Chen, Zhang;  Qian, Chen;  Wang, Jie;  Fu, Pan;  Zhao, Jizong
Adobe PDF(2827Kb)  |  收藏  |  浏览/下载：118/7  |  提交时间：2023/11/17
Drilling  Robots  Force  Robot sensing systems  Skull  Feeds  Service robots  Autonomous drilling  craniotomy robot  feed velocity and force constraint control  in vitro experiment  skull-dura boundary detection  
Multitask Policy Adversarial Learning for Human-Level Control With Large State Spaces 期刊论文
IEEE Transactions on Industrial Informatics Information, 2019, 卷号: 15, 期号: 4, 页码: 2395-2404
作者:  Wang JP(王军平);  You Kang Shi;  Wen Sheng Zhang;  Ian Thomas;  Shi Hui Duan
Adobe PDF(2547Kb)  |  收藏  |  浏览/下载：122/41  |  提交时间：2023/05/05
Decentralized Autonomous Operations and Organizations in TransVerse: Federated Intelligence for Smart Mobility 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 卷号: 53, 期号: 4, 页码: 2062-2072
作者:  Zhao, Chen;  Dai, Xingyuan;  Lv, Yisheng;  Niu, Jinglong;  Lin, Yilun
Adobe PDF(1921Kb)  |  收藏  |  浏览/下载：245/4  |  提交时间：2023/02/22
Intelligent Transportation Systems (ITS)  Artificial Systems, Computational Experiments, Parallel Execution (ACP)  Cyber–Physical–Social Systems (CPSS)  
Adaptive model-based dynamic event-triggered output feedback control of a robotic manipulator with disturbance 期刊论文
ISATransactions, 2021, 页码: 64-78
作者:  Gao jie;  Kang Erlong;  He Wei;  Qiao hong
Adobe PDF(2719Kb)  |  收藏  |  浏览/下载：274/99  |  提交时间：2022/06/14
A novel event-triggered adaptive tracking control framework for a manipulator with aperiodic neural network estimation 期刊论文
Assembly Automation, 2022, 页码: 1-16
作者:  Gao jie
Adobe PDF(2045Kb)  |  收藏  |  浏览/下载：255/86  |  提交时间：2022/06/14
Fixed-Time Adaptive Fuzzy Control for Uncertain Nonstrict-Feedback Systems with Time-Varying Constraints and Input Saturations 期刊论文
IEEE Transactions on Fuzzy Systems, 2022, 卷号: 30, 期号: 4, 页码: 1114-1128
作者:  Jinlin Su;  Jianqiang Yi;  Zhiqiang Pu
Adobe PDF(1378Kb)  |  收藏  |  浏览/下载：283/62  |  提交时间：2022/04/02
Adaptive fuzzy control  fixed-time control  input saturation  nonstrict-feedback systems  time-varying constraints  
Trip Purposes Mining From Mobile Signaling Data 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 卷号: 99, 期号: 99, 页码: 13
作者:  Li, Zhishuai;  Xiong, Gang;  Wei, Zebing;  Zhang, Yu;  Zheng, Meng;  Liu, Xiaoli;  Tarkoma, Sasu;  Huang, Min;  Lv, Yisheng;  Wu, Chuheng
Adobe PDF(3962Kb)  |  收藏  |  浏览/下载：423/75  |  提交时间：2022/01/27
Cellular networks  Trajectory  Semantics  Unsupervised learning  Supervised learning  Resource management  Public transportation  Trip purpose inference  cellular network data  latent Dirichlet allocation  travel behavior  big data  
Adaptive Critic Learning for Constrained Optimal Event-Triggered Control With Discounted Cost 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 1, 页码: 91-104
作者:  Yang, Xiong;  Wei, Qinglai
收藏  |  浏览/下载：213/0  |  提交时间：2021/06/15
Nonlinear systems  Optimal control  Robustness  Cost function  Adaptive systems  Adaptive critic designs (ACDs)  adaptive critic learning (ACL)  adaptive dynamic programming (ADP)  constrained optimal control  event-triggered control (ETC)  reinforcement learning (RL)