AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (1.1 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Generalized fault estimator-based prescribed performance control for a class of strict-feedback nonlinear systems

Xuechao Zhang1,2Shichang Lu2( )
School of Economics and Law, University of Science and Technology Liaoning, Anshan, Liaoning, China
School of Business Administration, Liaoning Technical University, Huludao, Liaoning, China
Show Author Information

Abstract

This paper addresses fault estimation and prescribed performance control for strict-feedback nonlinear systems subject to unknown time-varying faults. By introducing a novel intermediate variable for fault estimation, an adaptive fault estimator and a fault-tolerant controller are proposed. Utilizing a proof by contradiction, the designed prescribed performance control scheme resolves the complex coupling between fault estimation and adaptive control. Furthermore, all closed-loop signals are proven bounded, with both tracking and state errors converging to predesigned compact sets. Finally, numerical simulation on a single-link robot system validates the effectiveness of the proposed algorithm.

CLC number: 93D21, 93C10

References

【1】
【1】
 
 
AIMS Mathematics
Pages 18337-18355

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Zhang X, Lu S. Generalized fault estimator-based prescribed performance control for a class of strict-feedback nonlinear systems. AIMS Mathematics, 2025, 10(8): 18337-18355. https://doi.org/10.3934/math.2025819

1

Views

0

Downloads

0

Crossref

0

Web of Science

0

Scopus

Received: 21 June 2025
Revised: 27 July 2025
Accepted: 06 August 2025
Published: 15 August 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)