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

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

科研成果: 期刊稿件文章同行评审

35 引用 (Scopus)

摘要

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.

源语言英语
页(从-至)1178-1188
页数11
期刊IEEE Transactions on Cybernetics
54
2
DOI
出版状态已出版 - 1 2月 2024

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