Adaptive Optimal Control via Continuous-Time <i>Q</i>-Learning for Stackelberg–Nash Games of Uncertain Nonlinear Systems-Reference-Cited by-同舟云学术

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Adaptive Optimal Control via Continuous-Time Q-Learning for Stackelberg–Nash Games of Uncertain Nonlinear Systems

Published:2024-07 Issue:7 Volume:54 Page:4461-4470
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Yu Shuhang¹^ORCID,Zhang Huaguang²^ORCID,Ming Zhongyang¹^ORCID,Sun Jiayue¹^ORCID

Affiliation:

1. School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China

2. State Key Laboratory of Synthetical Automation for Process Industries and the School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Liaoning Revitalization Talents Program

Nature Science Foundation of Liaoning Province of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221021/10559915/10500825.pdf?arnumber=10500825

Reference28 articles.

1. Distributed Optimal Fault Estimation and Fault-Tolerant Control for Interconnected Systems: A Stackelberg Differential Graphical Game Approach

2. Event-Triggered Robust Adaptive Dynamic Programming for Multiplayer Stackelberg–Nash Games of Uncertain Nonlinear Systems

3. Dynamic Self-Triggered Controller Codesign for Markov Jump Systems

4. Robust $H_{\infty}$ Fuzzy Control Approach for a Class of Markovian Jump Nonlinear Systems

5. Optimal Control for Unknown Discrete-Time Nonlinear Markov Jump Systems Using Adaptive Dynamic Programming

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