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Adaptive Optimal Output Regulation of Interconnected Singularly Perturbed Systems With Application to Power Systems
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 3, 页码: 595-607
作者:
Jianguo Zhao
;
Chunyu Yang
;
Weinan Gao
;
Linna Zhou
;
Xiaomin Liu
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2024/02/19
Adaptive optimal control
decentralized control
output regulation
reinforcement learning (RL)
singularly perturbed systems (SPSs)
A Novel Disturbance Observer Based Fixed-Time Sliding Mode Control for Robotic Manipulators With Global Fast Convergence
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 3, 页码: 661-672
作者:
Dan Zhang
;
Jiabin Hu
;
Jun Cheng
;
Zheng-Guang Wu
;
Huaicheng Yan
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  |  
浏览/下载:0/0
  |  
提交时间:2024/02/19
Disturbance observer (DO)
fixed-time
non-singular sliding mode control
robotic manipulator
trajectory tracking
Decentralized Optimal Control and Stabilization of Interconnected Systems With Asymmetric Information
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 3, 页码: 698-707
作者:
Na Wang
;
Xiao Liang
;
Hongdan Li
;
Xiao Lu
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  |  
浏览/下载:1/0
  |  
提交时间:2024/02/19
Asymmetric information
decentralized control
forward-backward stochastic difference equations
interconnected system
stalibization
Autonomous Vehicle Platoons In Urban Road Networks: A Joint Distributed Reinforcement Learning and Model Predictive Control Approach
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 1, 页码: 141-156
作者:
Luigi D’Alfonso
;
Francesco Giannini
;
Giuseppe Franzè
;
Giuseppe Fedele
;
Francesco Pupo
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  |  
浏览/下载:2/0
  |  
提交时间:2024/01/02
Distributed model predictive control
distributed reinforcement learning
routing decisions
urban road networks
Autogeneration of Mission-Oriented Robot Controllers Using Bayesian-Based Koopman Operator
期刊论文
IEEE TRANSACTIONS ON ROBOTICS, 2024, 卷号: 40, 页码: 903-918
作者:
Pan, Jie
;
Li, Dongyue
;
Wang, Jian
;
Zhang, Pengfei
;
Shao, Jinyan
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  |  
浏览/下载:2/0
  |  
提交时间:2024/02/21
Bayesian optimization (BO)
control-oriented model identification
Koopman operator
robot control
Event-Triggered-Based Consensus Neural Network Tracking Control for Nonlinear Pure-Feedback Multiagent Systems With Delayed Full-State Constraints
期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2023, 页码: 11
作者:
Wang, Xiao-An
;
Zhang, Guang-Ju
;
Niu, Ben
;
Wang, Ding
;
Wang, Xiao-Mei
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  |  
浏览/下载:0/0
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提交时间:2024/02/22
Nonlinear multiagent systems
delayed full state constraints
event-triggered design
asymptotic tracking control
adaptive control
Adaptive neuromuscular control of a simplified muscle tendon-driven musculoskeletal system
期刊论文
ROBOTIC INTELLIGENCE AND AUTOMATION, 2023, 页码: 13
作者:
Fan, Yerui
;
Wu, Yaxiong
;
Yuan, Jianbo
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浏览/下载:6/0
  |  
提交时间:2023/11/15
Musculoskeletal system
Adaptive neuromuscular control
Tendon-driven robot
Disturbance observer
Appointed-Time Control for Flexible Hypersonic Vehicles with Conditional Disturbance Negation
期刊论文
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2023, 卷号: 59, 期号: 5, 页码: 6327-6345
作者:
Sun, Jinlin
;
Pu, Zhiqiang
;
Chang, Yafei
;
Ding, Shihong
;
Yi, Jianqiang
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  |  
浏览/下载:0/0
  |  
提交时间:2024/02/22
Vehicle dynamics
Convergence
Control systems
Aerodynamics
Closed loop systems
Actuators
Mathematical models
Appointed-time control
conditional disturbance negation
hypersonic vehicle
input saturation
prescribed performance control
Adaptive Tracking Control of Robotic Manipulators With Unknown Kinematics and Uncertain Dynamics
期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2023, 页码: 18
作者:
Tong, Yuchuang
;
Liu, Jinguo
;
Zhou, Hao
;
Ju, Zhaojie
;
Zhang, Xin
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  |  
浏览/下载:3/0
  |  
提交时间:2023/11/16
Trajectory tracking
adaptive control
robotic manipulators
unknown kinematics model
uncertain dynamics
Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives
期刊论文
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 卷号: 8, 期号: 6, 页码: 3692-3711
作者:
Teng, Siyu
;
Hu, Xuemin
;
Deng, Peng
;
Li, Bai
;
Li, Yuchen
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  |  
浏览/下载:2/0
  |  
提交时间:2023/11/17
Motion planning
pipeline planning
end-to-end planning
imitation learning
reinforcement learning
parallel learning
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