Flexible Constraints-Based Adaptive Intelligent Event-Triggered Control for Slowly Switched Nonlinear Systems Using Reinforcement Learning-Reference-Cited by-同舟云学术

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Flexible Constraints-Based Adaptive Intelligent Event-Triggered Control for Slowly Switched Nonlinear Systems Using Reinforcement Learning

Published:2024-07 Issue:7 Volume:5 Page:3678-3689
ISSN:2691-4581
Container-title:IEEE Transactions on Artificial Intelligence
language:
Short-container-title:IEEE Trans. Artif. Intell.

Author:

Yan Chengyuan¹^ORCID,Xia Jianwei¹^ORCID,Park Ju H.²^ORCID,Xie Xiangpeng³^ORCID

Affiliation:

1. School of Mathematics Science, Liaocheng University, Liaocheng, China

2. Department of Electrical Engineering, Yeungnam University, Kyongsan, Republic of Korea

3. School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China

Funder

National Natural Science Foundation of China

Research Fund for the Taishan Scholar Project of Shandong Province of China

Natural Science Foundation of Shandong Province

National Research Foundation of Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9078688/10599850/10466651.pdf?arnumber=10466651

Reference45 articles.

1. Adaptive finite-time tracking control of full state constrained nonlinear systems with dead-zone

2. Adaptive Intelligent Controller Design-Based ISS Modular Approach for Uncertain Nonlinear Systems With Time-Varying Full-State Constraints

3. Removing the Feasibility Conditions Imposed on Tracking Control Designs for State-Constrained Strict-Feedback Systems

4. Adaptive Fuzzy Decentralized Dynamic Surface Control for Switched Large-Scale Nonlinear Systems With Full-State Constraints

5. Adaptive Tracking Control With Global Performance for Output-Constrained MIMO Nonlinear Systems

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