Adaptive resilient control of a class of nonlinear systems based on event-triggered mechanism

Journal article

Yang, Yang, Ge, Jingzhi, Yue, Dong, Meng, Qing and Wu, Jinran. (2020). Adaptive resilient control of a class of nonlinear systems based on event-triggered mechanism. Neurocomputing. 403, pp. 304-313. https://doi.org/10.1016/j.neucom.2020.04.061
AuthorsYang, Yang, Ge, Jingzhi, Yue, Dong, Meng, Qing and Wu, Jinran
Abstract

An event-triggered resilient control framework is proposed for a class of uncertain nonlinear systems under DoS attacks. Unknown dynamics are approximated by fuzzy logic systems (FLSs), while a switched adaptive state observer is presented to reconstruct unavailable states in the presence of intermittent attacks. Then, the backstepping method is developed for the control scheme; additionally, a relative threshold triggered scheme is designed. Furthermore, in theory, we prove the proposed control scheme guarantees all closed-loop signals remain bounded, and the error signal converges to a small area of the origin under DoS attacks. Finally, a power networked system and a numerical example are used to verify the effectiveness of the theoretical claims in our proposed scheme.

Keywordsevent-triggered scheme; nonlinear systems; resilient control; observer
Year2020
JournalNeurocomputing
Journal citation403, pp. 304-313
PublisherElsevier B.V.
ISSN0925-2312
Digital Object Identifier (DOI)https://doi.org/10.1016/j.neucom.2020.04.061
Scopus EID2-s2.0-85084639982
Page range304-313
Publisher's version
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All rights reserved
File Access Level
Controlled
Output statusPublished
Publication dates
Online20 Apr 2020
Publication process dates
Accepted09 Apr 2020
Deposited05 Jul 2023
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