Integral Action Feedback Design for Conservative Abstract Systems in the Presence of Input Nonlinearities

In this article, we present a stabilization feedback law with integral action for conservative abstract linear systems subjected to input nonlinearities. Based on the designed control law, we first prove the well-posedness using nonlinear semigroups theory and global asymptotic stability of the origin for the closed-loop system by constructing a weak Lyapunov functional. Secondly, as an illustration, we apply the results to a wave equation with integral action in two different cases: bounded control operator and unbounded control operator.

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Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2025-05-28
DOI
https://doi.org/10.1109/tac.2025.3574637
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Integral Action Feedback Design for Conservative Abstract Systems in the Presence of Input Nonlinearities

Cheng-Zhong Xu, Mathieu Bajodek, Xuyang Lou, Daniele Astolfi et al.
IEEE Transactions on Automatic Control
Neural Networks and Applications
article

Integral Action Feedback Design for Conservative Abstract Systems in the Presence of Input Nonlinearities

Cheng-Zhong Xu, Mathieu Bajodek, Xuyang Lou, Daniele Astolfi, Vincent Andrieu, Ling Ma
article en

Abstract

In this article, we present a stabilization feedback law with integral action for conservative abstract linear systems subjected to input nonlinearities. Based on the designed control law, we first prove the well-posedness using nonlinear semigroups theory and global asymptotic stability of the origin for the closed-loop system by constructing a weak Lyapunov functional. Secondly, as an illustration, we apply the results to a wave equation with integral action in two different cases: bounded control operator and unbounded control operator.

IEEE Transactions on Automatic ControlVol. 70(11)
Université Claude Bernard Lyon 1 (FR), Jiangnan University (CN), Centre National de la Recherche Scientifique (FR), Laboratoire d'Automatique, de Génie des Procédés et de Génie Pharmaceutique (FR)
Agence Nationale de la Recherche, China Scholarship Council
Openalex Percentile: Top 95%
Neural Networks and Applications
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