Event-triggered-based online integral reinforcement learning for optimal control of unknown constrained nonlinear systems-Reference-Cited by-同舟云学术

Event-triggered-based online integral reinforcement learning for optimal control of unknown constrained nonlinear systems

Published:2022-11-11 Issue: Volume: Page:1-13
ISSN:0020-7179
Container-title:International Journal of Control
language:en
Short-container-title:International Journal of Control

Author:

Han Xiumei¹^ORCID,Zhao Xudong¹^ORCID,Wang Ding²,Wang Bohui³

Affiliation:

1. Key Laboratory of Intelligent Control and Optimization for Industrial Equipment, Dalian University of Technology, Dalian, China

2. Beijing University of Technology, Faculty of Information, Beijing, People's Republic of China

3. Automation, Department of Automation, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai Jiao Tong University, Shanghai, People's Republic of China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

National Major Science and Technology Project

Liaoning Revitalization Talents Program

Beijing Natural Science Foundation

Publisher

Informa UK Limited

Subject

Computer Science Applications,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207179.2022.2137852

Reference39 articles.

1. Discrete-Time Nonlinear HJB Solution Using Approximate Dynamic Programming: Convergence Proof

2. Semi-global adaptive backstepping control for parametric strict-feedback systems with non-triangular structural uncertainties

3. Switched-observer-based adaptive output-feedback control design with unknown gain for pure-feedback switched nonlinear systems via average dwell time

4. Adaptive Actor–Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances

5. Distributed optimal control for continuous-time nonaffine nonlinear interconnected systems

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