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浏览/检索结果:
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Event-Triggered Bipartite Consensus Tracking and Vibration Control of Flexible Timoshenko Manipulators Under Time-Varying Actuator Faults
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 5, 页码: 1190-1201
作者:
Xiangqian Yao
;
Hao Sun
;
Zhijia Zhao
;
Yu Liu
收藏
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浏览/下载:0/0
  |  
提交时间:2024/04/10
Bipartite consensus tracking
event-triggered control
multiple manipulators
neural networks
time-varying actuator faults
Fully Distributed Nash Equilibrium Seeking for High-Order Players With Actuator Limitations
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 6, 页码: 1434-1444
作者:
Maojiao Ye
;
Qing-Long Han
;
Lei Ding
;
Shengyuan Xu
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  |  
浏览/下载:8/0
  |  
提交时间:2023/05/29
Actuator limitation
directed networks
games
Nash equilibrium
New design of active disturbance rejection control for nonlinear uncertain systems with unknown control input gain
期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2022, 卷号: 65, 期号: 4, 页码: 13
作者:
Chen, Sen
;
Chen, Zhixiang
;
Huang, Yi
;
Zhao, Zhi-Liang
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  |  
浏览/下载:24/0
  |  
提交时间:2022/04/02
uncertain system
active disturbance rejection control
control input gain
DISTRIBUTED ORDER ESTIMATION OF ARX MODEL UNDER
期刊论文
SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2022, 卷号: 60, 期号: 3, 页码: 1519-1545
作者:
Gan, D. I. E.
;
Liu, Zhixin
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  |  
浏览/下载:1/0
  |  
提交时间:2023/02/07
distributed order estimation
cooperative excitation condition
distributed least squares
convergence
Channel erosion dominates sediment sources in an agricultural catchment in the Upper Yangtze basin of China: Evidence from geochemical fingerprints
期刊论文
CATENA, 2021, 卷号: 199, 页码: 14
作者:
Shi, Zhonglin
;
Blake, William H.
;
Wen, Anbang
;
Chen, Jiacun
;
Yan, Dongchun
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  |  
浏览/下载:113/0
  |  
提交时间:2021/03/08
Sediment tracing
Geochemical fingerprinting
Soil conservation
Sediment sources
Channel erosion
Particle size
Asymmetric Bounded Neural Control for an Uncertain Robot by State Feedback and Output Feedback
期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 3, 页码: 1735-1746
作者:
Kong, Linghuan
;
He, Wei
;
Dong, Yiting
;
Cheng, Long
;
Yang, Chenguang
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  |  
浏览/下载:23/0
  |  
提交时间:2021/03/29
Neural networks
Adaptive systems
Nonlinear systems
Manipulator dynamics
Uncertainty
adaptive control
asymmetrically bounded inputs
neural networks
robotic manipulator
Neural-Network-Based Control for Discrete-Time Nonlinear Systems with Input Saturation Under Stochastic Communication Protocol
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 8, 期号: 4, 页码: 766-778
作者:
Xueli Wang
;
Derui Ding
;
Hongli Dong
;
Xian-Ming Zhang
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  |  
浏览/下载:28/0
  |  
提交时间:2021/04/09
Adaptive dynamic programming (ADP)
constrained inputs
neural network (NN)
stochastic communication protocols (SCPs)
suboptimal control
Learning-Based Error-Constrained Motion Control for Pneumatic Artificial Muscle-Actuated Exoskeleton Robots With Hardware Experiments
期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2021, 页码: 1-12
作者:
Yang, Tong
;
Chen YH( 陈轶珩)
;
Sun N(孙宁)
;
Liu LQ(刘连庆)
;
Qin, Yanding
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  |  
浏览/下载:21/0
  |  
提交时间:2021/12/31
Robots
Exoskeletons
Tracking
Safety
Pneumatic systems
Hysteresis
Muscles
Pneumatic artificial muscles
motion control
mechatronics
Lyapunov techniques
Reinforcement Learning-Based Optimal Stabilization for Unknown Nonlinear Systems Subject to Inputs With Uncertain Constraints
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 10, 页码: 4330-4340
作者:
Zhao, Bo
;
Liu, Derong
;
Luo, Chaomin
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  |  
浏览/下载:34/0
  |  
提交时间:2021/01/07
Nonlinear systems
Optimal control
Artificial neural networks
Actuators
Observers
Feedforward systems
Adaptive dynamic programming (ADP)
neural networks (NNs)
optimal control
reinforcement learning (RL)
uncertain input constraints
unknown nonlinear systems
PIF1 and RVE1 form a transcriptional feedback loop to control light-mediated seed germination in Arabidopsis
期刊论文
JOURNAL OF INTEGRATIVE PLANT BIOLOGY, 2020, 卷号: 62, 期号: 9, 页码: 1372-1384
作者:
Yang, Liwen
;
Jiang, Zhimin
;
Jing, Yanjun
;
Lin, Rongcheng
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  |  
浏览/下载:15/0
  |  
提交时间:2022/03/01
phytochrome
seed germination
transcription factor
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