Data-Driven Event-Triggered Adaptive Dynamic Programming Control for Nonlinear Systems with Input Saturation

Mouquan Shen; Xianming Wang; Song Zhu; Zhengguang Wu; Tingwen Huang

doi:10.1109/TCYB.2023.3337779

Data-Driven Event-Triggered Adaptive Dynamic Programming Control for Nonlinear Systems with Input Saturation

Mouquan Shen, Xianming Wang, Song Zhu, Zhengguang Wu, Tingwen Huang

COLLEGE OF ELECTRICAL ENGINEERING AND CONTROL SCIENCE

Research output: Contribution to journal › Article › peer-review

35 Scopus citations

Abstract

This article is devoted to data-driven event-triggered adaptive dynamic programming (ADP) control for nonlinear systems under input saturation. A global optimal data-driven control law is established by the ADP method with a modified index. Compared with the existing constant penalty factor, a dynamic version is constructed to accelerate error convergence. A new triggering mechanism covering existing results as special cases is set up to reduce redundant triggering events caused by emergent factors. The uniformly ultimate boundedness of error system is established by the Lyapunov method. The validity of the presented scheme is verified by two examples.

Original language	English
Pages (from-to)	1178-1188
Number of pages	11
Journal	IEEE Transactions on Cybernetics
Volume	54
Issue number	2
DOIs	https://doi.org/10.1109/TCYB.2023.3337779
State	Published - 1 Feb 2024

Keywords

Adaptive dynamic programming (ADP)
data-driven control (DDC)
event-triggered (ET) control

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10.1109/TCYB.2023.3337779

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title = "Data-Driven Event-Triggered Adaptive Dynamic Programming Control for Nonlinear Systems with Input Saturation",

abstract = "This article is devoted to data-driven event-triggered adaptive dynamic programming (ADP) control for nonlinear systems under input saturation. A global optimal data-driven control law is established by the ADP method with a modified index. Compared with the existing constant penalty factor, a dynamic version is constructed to accelerate error convergence. A new triggering mechanism covering existing results as special cases is set up to reduce redundant triggering events caused by emergent factors. The uniformly ultimate boundedness of error system is established by the Lyapunov method. The validity of the presented scheme is verified by two examples.",

keywords = "Adaptive dynamic programming (ADP), data-driven control (DDC), event-triggered (ET) control",

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AB - This article is devoted to data-driven event-triggered adaptive dynamic programming (ADP) control for nonlinear systems under input saturation. A global optimal data-driven control law is established by the ADP method with a modified index. Compared with the existing constant penalty factor, a dynamic version is constructed to accelerate error convergence. A new triggering mechanism covering existing results as special cases is set up to reduce redundant triggering events caused by emergent factors. The uniformly ultimate boundedness of error system is established by the Lyapunov method. The validity of the presented scheme is verified by two examples.

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Data-Driven Event-Triggered Adaptive Dynamic Programming Control for Nonlinear Systems with Input Saturation

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