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检索条件"任意字段=IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning"
1018 条 记 录,以下是431-440 订阅
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Neural Network Tracking Control of Unknown Servo System with Approximate dynamic programming
Neural Network Tracking Control of Unknown Servo System with...
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第三十八届中国控制会议
作者: Yongfeng Lv Xuemei Ren Tianyi Zeng Linwei Li Jing Na School of Automation Beijing Institute of Technology IEEE Faculty of Mechanical & Electrical Engineering Kunming University of Science & Technology
Although the adaptive dynamic programming(ADP) scheme has been widely researched on the optimal problem in recent years, which has not been applied to the servo system. In this paper, a simplified reinforcement learni... 详细信息
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adaptive dynamic programming Based Motion Control of Autonomous Underwater Vehicles  5
Adaptive Dynamic Programming Based Motion Control of Autonom...
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5th International Conference on Control, Decision and Information Technologies (CoDIT)
作者: Vibhute, Siddhant VJTI Dept Elect Engn Mumbai Maharashtra India
In this paper, adaptive dynamic programming (ADP) technique is utilized to achieve optimal motion control of Autonomous Underwater Vehicle (AUV) System. The paper proposes a model-free based method that takes into con... 详细信息
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adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure
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ieee TRANSACTIONS ON NEURAL NETWORKS AND learning SYSTEMS 2018年 第6期29卷 2099-2111页
作者: Luo, Biao Liu, Derong Wu, Huai-Ning Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China Beihang Univ Sci & Technol Aircraft Control Lab Beijing 100191 Peoples R China
reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time syste... 详细信息
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adaptive dynamic programming for Cooperative Control with Incomplete Information
Adaptive Dynamic Programming for Cooperative Control with In...
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ieee International Conference on Systems, Man, and Cybernetics (SMC)
作者: Koepf, Florian Ebbert, Sebastian Flad, Michael Hohmann, Soeren Karlsruhe Inst Technol Inst Control Syst IRS Karlsruhe Germany
There is a trend towards interconnected and complex dynamical systems that are controlled by more than one controller. Due to the coupling of the controllers by means of the system, these interacting controllers need ... 详细信息
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reinforcement learning for adaptive Periodic Linear Quadratic Control
Reinforcement Learning for Adaptive Periodic Linear Quadrati...
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ieee Annual Conference on Decision and Control
作者: Bo Pang Zhong-Ping Jiang Iven Mareels Control and Networks Lab Department of Electrical and Computer Engineering Tandon School of Engineering New York University Brooklyn NY USA IBM Research - Australia Melbourne Vic Australia
This paper presents a first solution to the problem of adaptive LQR for continuous-time linear periodic systems. Specifically, reinforcement learning and adaptive dynamic programming (ADP) techniques are used to devel... 详细信息
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Optimal Fault-Tolerant Control for Discrete-Time Nonlinear Strict-Feedback Systems Based on adaptive Critic Design
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ieee TRANSACTIONS ON NEURAL NETWORKS AND learning SYSTEMS 2018年 第6期29卷 2179-2191页
作者: Wang, Zhanshan Liu, Lei Wu, Yanming Zhang, Huaguang Northeastern Univ Sch Informat Sci & Engn Shenyang 110004 Liaoning Peoples R China State Key Lab Synthet Automat Proc Ind Shenyang 110819 Liaoning Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Liaoning Peoples R China Liaoning Univ Technol Coll Sci Jinzhou 121001 Peoples R China
This paper investigates the problem of optimal fault-tolerant control (FTC) for a class of unknown nonlinear discrete-time systems with actuator fault in the framework of adaptive critic design (ACD). A pivotal highli... 详细信息
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Development of reinforcement learning Algorithm for 2-DOF Helicopter Model  27
Development of Reinforcement Learning Algorithm for 2-DOF He...
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27th ieee International symposium on Industrial Electronics, ISIE 2018
作者: Fandel, Andrew Birge, Anthony Miah, Suruz Department Bradley University Electrical and Computer Engineering PeoriaIL United States
This paper examines a reinforcement learning strategy for controlling a two degree-of-freedom (2-DOF) helicopter. The pitch and yaw angles are regulated to their corresponding reference angles by applying appropriate ... 详细信息
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reinforcement learning Solution with Costate Approximation for a Flexible Wing Aircraft  23
Reinforcement Learning Solution with Costate Approximation f...
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ieee International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
作者: Abouheaf, Mohammed Gueaieb, Wail Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada
An online adaptive learning approach based on costate function approximation is developed to solve an optimal control problem in real time. The proposed approach tackles the main concerns associated with the classical... 详细信息
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Special Issue on Deep reinforcement learning and adaptive dynamic programming
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ieee TRANSACTIONS ON NEURAL NETWORKS AND learning SYSTEMS 2018年 第6期29卷 2038-2041页
作者: Zhao, Dongbin Liu, Derong Lewis, F. L. Principe, Jose C. Squartini, Stefano Chinese Acad Sci Inst Automat Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Univ Arizona Tucson AZ USA IEEE Computat Intelligence Soc Adapt Dynam Programming & Reinforcement Learning Piscataway NJ USA IEEE Computat Intelligence Soc Multimedia Subcomm Piscataway NJ USA Beijing Chapter Beijing Peoples R China Univ Illinois Elect & Comp Engn & Comp Sci Chicago IL USA Int Neural Network Soc Hoffman Estates IL USA Int Assoc Pattern Recognit Hoffman Estates IL USA Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Nanjing Univ Sci & Technol Nanjing Jiangsu Peoples R China Northeastern Univ Shenyang Liaoning Peoples R China Natl Acad Inventors Tampa FL USA IFAC Geneva Switzerland PE Texas UK Inst Measurement & Control Austin TX USA Univ Texas Arlington Arlington TX 76019 USA Univ Florida Elect & Comp Engn & Biomed Engn Gainesville FL USA Univ Florida ECE Gainesville FL USA Univ Florida Computat NeuroEngn Lab CNEL Gainesville FL USA Univ Florida Advisory Board Inst Brain Gainesville FL USA IEEE Signal Proc Soc Tech Comm Neural Networks Piscataway NJ USA UnivPM Dept Informat Engn Elect Circuit Theory Ancona Italy UnivPM Ancona Italy
In the first issue of Nature 2015, Google DeepMind published a paper “Human-level control through deep reinforcement learning.” Furthermore, in the first issue of Nature 2016, it published a cover paper “Master... 详细信息
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PDP: Parallel dynamic programming
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ieee/CAA Journal of Automatica Sinica 2017年 第1期4卷 1-5页
作者: Fei-Yue Wang Jie Zhang Qinglai Wei Xinhu Zheng Li Li IEEE State Key Laboratory of Management and Control for Complex Systems(SKL-MCCS) Institute of AutomationChinese Academy of Sciences(CASIA) School of Computer and Control Engineering University of Chinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences(SKL-MCCSCASIA) Qingdao Academy of Intelligent Industries Department of Computer Science and Engineering University of Minnesota Department of Automation Tsinghua University
Deep reinforcement learning is a focus research area in artificial intelligence. The principle of optimality in dynamic programming is a key to the success of reinforcement learning methods. The principle of adaptive ... 详细信息
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