Event-triggered data-driven control of discrete-time nonlinear systems with unknown disturbance

Xianming Wang; Wen Qin; Ju H. Park; Mouquan Shen

doi:10.1016/j.isatra.2021.11.026

Event-triggered data-driven control of discrete-time nonlinear systems with unknown disturbance

Xianming Wang, Wen Qin, Ju H. Park, Mouquan Shen

电气工程与控制科学学院

科研成果: 期刊稿件 › 文章 › 同行评审

12 引用（Scopus）

摘要

This paper is dedicated to event-triggered data-driven control of nonlinear systems with unknown disturbance via model free iterative learning approach. An extended state observer is employed to reconstruct the disturbance in system output. An event-triggered model free iterative learning control strategy is constructed by system input, system output and the reconstructed disturbance. Sufficient conditions are proposed to make the resultant tracking error system be uniform ultimate bounded. Simulation examples are provided to validate the effectiveness of the proposed scheme.

源语言	英语
页（从-至）	256-264
页数	9
期刊	ISA Transactions
卷	128
DOI	https://doi.org/10.1016/j.isatra.2021.11.026
出版状态	已出版 - 9月 2022

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abstract = "This paper is dedicated to event-triggered data-driven control of nonlinear systems with unknown disturbance via model free iterative learning approach. An extended state observer is employed to reconstruct the disturbance in system output. An event-triggered model free iterative learning control strategy is constructed by system input, system output and the reconstructed disturbance. Sufficient conditions are proposed to make the resultant tracking error system be uniform ultimate bounded. Simulation examples are provided to validate the effectiveness of the proposed scheme.",

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author = "Xianming Wang and Wen Qin and Park, {Ju H.} and Mouquan Shen",

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AU - Qin, Wen

AU - Park, Ju H.

AU - Shen, Mouquan

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AB - This paper is dedicated to event-triggered data-driven control of nonlinear systems with unknown disturbance via model free iterative learning approach. An extended state observer is employed to reconstruct the disturbance in system output. An event-triggered model free iterative learning control strategy is constructed by system input, system output and the reconstructed disturbance. Sufficient conditions are proposed to make the resultant tracking error system be uniform ultimate bounded. Simulation examples are provided to validate the effectiveness of the proposed scheme.

KW - Event-triggered control

KW - Extended state observer

KW - Networked control systems

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JF - ISA Transactions

ER -

Event-triggered data-driven control of discrete-time nonlinear systems with unknown disturbance

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