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Auditory Feature Driven Model Predictive Control for Sound Source Approaching 期刊论文
International Journal of Control, Automation, and Systems, 2023, 卷号: 22, 期号: 2, 页码: 1-14
作者:  Wang, Zhiqing;  Zou, Wei;  Zhang, Wei;  Ma, Hongxuan;  Zhang, Chi;  Guo, Yuxin
Adobe PDF(7966Kb)  |  收藏  |  浏览/下载：180/50  |  提交时间：2023/06/20
Source approaching control, interaural time difference, robotic audition, sound source localization.  
Velocity and input constrained distributed nash equilibrium seeking for multi-agent integrated game and control via event-triggered communication 期刊论文
NONLINEAR DYNAMICS, 2022, 卷号: 109, 页码: 2781-2798
作者:  Pu, Zhiqiang;  Ai, Xiaolin;  Yi, Jianqiang
Adobe PDF(1775Kb)  |  收藏  |  浏览/下载：265/31  |  提交时间：2022/07/25
Multi-agent systems  Integrated game and control  Velocity constraint  Input saturation  Event-triggered communication  
Practical Robotic Auditory Perception and Approaching Methods Based on Small-sized Microphone Array 期刊论文
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2022, 页码: 1-16
作者:  Wang, Zhiqing;  Zou, Wei;  Zhang, Chi;  Kang, Zhaobing;  Zhu, Jiagang
Adobe PDF(9439Kb)  |  收藏  |  浏览/下载：227/27  |  提交时间：2022/06/10
Aural feature extraction  robotic audition  sound source localization  source approaching control  
Missile guidance with assisted deep reinforcement learning for head-on interception of maneuvering target 期刊论文
COMPLEX & INTELLIGENT SYSTEMS, 2021, 页码: 12
作者:  Li, Weifan;  Zhu, Yuanheng;  Zhao, Dongbin
Adobe PDF(1431Kb)  |  收藏  |  浏览/下载：285/51  |  提交时间：2021/12/28
Reinforcement learning  Missile guidance  Auxiliary learning  Self-imitation learning  
Structure transforming for constructing constraint force field in musculoskeletal robot 期刊论文
ASSEMBLY AUTOMATION, 2021, 页码: 12
作者:  Zhong, Shanlin;  Chen, Ziyu;  Zhou, Junjie
Adobe PDF(2152Kb)  |  收藏  |  浏览/下载：312/58  |  提交时间：2021/12/28
High precision  Attractive region in environment  Constraint force field  Musculoskeletal robot  
Adaptive-Neural-Network-Based Trajectory Tracking Control for a Nonholonomic Wheeled Mobile Robot With Velocity Constraints 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 卷号: 68, 期号: 6, 页码: 5057-5067
作者:  Chen, Ziyu;  Liu, Yang;  He, Wei;  Qiao, Hong;  Ji, Haibo
收藏  |  浏览/下载：284/0  |  提交时间：2021/04/06
Mobile robots  Lyapunov methods  Adaptive systems  Artificial neural networks  Automation  Adaptive neural networks  barrier Lyapunov function (BLF)  velocity constraint  wheeled mobile robot (WMR)  
Neural network-based model predictive tracking control of an uncertain robotic manipulator with input constraints 期刊论文
ISA TRANSACTIONS, 2021, 卷号: 109, 页码: 89-101
作者:  Kang, Erlong;  Qiao, Hong;  Gao, Jie;  Yang, Wenjing
Adobe PDF(942Kb)  |  收藏  |  浏览/下载：358/69  |  提交时间：2021/03/29
Model predictive control  Neural network  Robotic manipulator  Unknown dynamics  Online learning estimation  Input constraints  
Joint Learning in the Spatio-Temporal and Frequency Domains for Skeleton-Based Action Recognition 期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2020, 卷号: 22, 期号: 9, 页码: 2207-2220
作者:  Guyue, Hu;  Bo, Cui;  Shan, Yu
Adobe PDF(4803Kb)  |  收藏  |  浏览/下载：296/57  |  提交时间：2020/09/28
Skeleton-based Action Recognition  Frequency Attention  Synchronous Local and Non-local Learning  Soft-margin Focal Loss  Pesudo Multi-task Learning  
Computational modeling of Emotion-motivated Decisions for Continuous Control of Mobile Robots 期刊论文
IEEE Transactions on Cognitive and Developmental Systems, 2020, 卷号: 13, 期号: 2020, 页码: 1-14
作者:  Huang, Xiao;  Wu, Wei;  Qiao, Hong
浏览  |  Adobe PDF(5970Kb)  |  收藏  |  浏览/下载：251/87  |  提交时间：2020/06/09
Brain-inspired Computing  Emotion-motivated Learning  Emotion-memory Interactions  Decision-making  Reinforcement Learning  
Connecting Model-Based and Model-Free Control With Emotion Modulation in Learning Systems 期刊论文
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, 卷号: 10, 期号: 4, 页码: 1-15
作者:  Huang, Xiao;  Wu, Wei;  Qiao, Hong
浏览  |  Adobe PDF(1614Kb)  |  收藏  |  浏览/下载：263/89  |  提交时间：2020/06/09
Brain-inspired computing  decision-making  emotion modulation  emotion-cognition interactions  reinforcement learning