Online Off-Policy Reinforcement Learning for Optimal Control of Unknown Nonlinear Systems Using Neural Networks-Reference-Cited by-同舟云学术

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Online Off-Policy Reinforcement Learning for Optimal Control of Unknown Nonlinear Systems Using Neural Networks

Published:2024-08 Issue:8 Volume:54 Page:5112-5122
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Zhu Liao¹^ORCID,Wei Qinglai²^ORCID,Guo Ping¹^ORCID

Affiliation:

1. International Academic Center of Complex Systems, Beijing Normal University, Zhuhai, China

2. State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

Funder

National Key Reseanch and Development Program of China

National Natural Science Foundation of China

Science and Technology Development Fund, Macau, SAR

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221021/10604682/10528363.pdf?arnumber=10528363

Reference46 articles.

1. Optimal Control

2. Adaptive Dynamic Programming for Control

3. Adaptive Dynamic Programming with Applications in Optimal Control

4. Reinforcement Learning: An Introduction

5. Adaptive Dynamic Programming for Control: A Survey and Recent Advances

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1. Optimal robust online tracking control for space manipulator in task space using off-policy reinforcement learning;Aerospace Science and Technology;2024-10

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