Prescribed-Time Input-to-State Stabilization of Normal Nonlinear Systems by Bounded Time-Varying Feedback

Kang Kang Zhang; Bin Zhou; Guang Ren Duan

doi:10.1109/TCSI.2022.3182884

Prescribed-Time Input-to-State Stabilization of Normal Nonlinear Systems by Bounded Time-Varying Feedback

Kang Kang Zhang
, Bin Zhou^*
, Guang Ren Duan

^*Corresponding author for this work

School of Astronautics

Harbin Institute of Technology

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

47 Scopus citations

Abstract

This paper studies the prescribed-time input-to-state stabilization problem of normal nonlinear systems. With the help of some key properties of a class of parametric Lyapunov equations, the prescribed-time input-to-state stabilization problem of normal nonlinear systems under matched uncertainties is studied. Some bounded time-varying controllers are proposed. It is shown that the closed-loop systems are prescribed-time input-to-state stable. Finally, the effectiveness of the established methods is illustrated by two physical systems.

Original language	English
Pages (from-to)	3715-3725
Number of pages	11
Journal	IEEE Transactions on Circuits and Systems
Volume	69
Issue number	9
DOIs	https://doi.org/10.1109/TCSI.2022.3182884
State	Published - 1 Sep 2022

Keywords

Normal nonlinear systems
bounded feedback
input-to-state stability
prescribed-time input-to-state stabilization
time-varying feedback

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10.1109/TCSI.2022.3182884

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title = "Prescribed-Time Input-to-State Stabilization of Normal Nonlinear Systems by Bounded Time-Varying Feedback",

abstract = "This paper studies the prescribed-time input-to-state stabilization problem of normal nonlinear systems. With the help of some key properties of a class of parametric Lyapunov equations, the prescribed-time input-to-state stabilization problem of normal nonlinear systems under matched uncertainties is studied. Some bounded time-varying controllers are proposed. It is shown that the closed-loop systems are prescribed-time input-to-state stable. Finally, the effectiveness of the established methods is illustrated by two physical systems.",

keywords = "Normal nonlinear systems, bounded feedback, input-to-state stability, prescribed-time input-to-state stabilization, time-varying feedback",

author = "Zhang, \{Kang Kang\} and Bin Zhou and Duan, \{Guang Ren\}",

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AU - Zhang, Kang Kang

AU - Zhou, Bin

AU - Duan, Guang Ren

PY - 2022/9/1

Y1 - 2022/9/1

N2 - This paper studies the prescribed-time input-to-state stabilization problem of normal nonlinear systems. With the help of some key properties of a class of parametric Lyapunov equations, the prescribed-time input-to-state stabilization problem of normal nonlinear systems under matched uncertainties is studied. Some bounded time-varying controllers are proposed. It is shown that the closed-loop systems are prescribed-time input-to-state stable. Finally, the effectiveness of the established methods is illustrated by two physical systems.

AB - This paper studies the prescribed-time input-to-state stabilization problem of normal nonlinear systems. With the help of some key properties of a class of parametric Lyapunov equations, the prescribed-time input-to-state stabilization problem of normal nonlinear systems under matched uncertainties is studied. Some bounded time-varying controllers are proposed. It is shown that the closed-loop systems are prescribed-time input-to-state stable. Finally, the effectiveness of the established methods is illustrated by two physical systems.

KW - Normal nonlinear systems

KW - bounded feedback

KW - input-to-state stability

KW - prescribed-time input-to-state stabilization

KW - time-varying feedback

UR - https://www.scopus.com/pages/publications/85133747324

U2 - 10.1109/TCSI.2022.3182884

DO - 10.1109/TCSI.2022.3182884

M3 - 文章

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SN - 1549-8328

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SP - 3715

EP - 3725

JO - IEEE Transactions on Circuits and Systems

JF - IEEE Transactions on Circuits and Systems

IS - 9

ER -

Prescribed-Time Input-to-State Stabilization of Normal Nonlinear Systems by Bounded Time-Varying Feedback

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