Robust Output Regulation and Reinforcement Learning-Based Output Tracking Design for Unknown Linear Discrete-Time Systems-Reference-Cited by-同舟云学术

Robust Output Regulation and Reinforcement Learning-Based Output Tracking Design for Unknown Linear Discrete-Time Systems

Published:2023-04 Issue:4 Volume:68 Page:2391-2398
ISSN:0018-9286
Container-title:IEEE Transactions on Automatic Control
language:
Short-container-title:IEEE Trans. Automat. Contr.

Author:

Chen Ci¹^ORCID,Xie Lihua²^ORCID,Jiang Yi³^ORCID,Xie Kan⁴^ORCID,Xie Shengli⁵^ORCID

Affiliation:

1. School of Automation, Guangdong Key Laboratory of IoT Information Technology, Guangdong University of Technology, Guangzhou, China

2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

3. Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China

4. School of Automation, 111 Center for Intelligent Batch Manufacturing Based on IoT Technology, Guangdong University of Technology, Guangzhou, China

5. Key Laboratory of Intelligent Information Processing and System Integration of IoT, Ministry of Education, Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing, Guangzhou, China

Funder

National Natural Science Foundation of China

State Key Laboratory of Synthetical Automation for Process Industries

Wallenberg-NTU Presidential Postdoctoral Fellowship

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9/10084346/09769938.pdf?arnumber=9769938

Reference38 articles.

1. Off-policy learning for adaptive optimal output synchronization of heterogeneous multi-agent systems

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