EconPapers    
Economics at your fingertips  
 

A resilient optimized dynamic event-triggered mechanism on networked control system with switching behavior under mixed attacks

Yan Ma, Zhenzhen Zhang, Li Yang, Hao Chen and Yihao Zhang

Applied Mathematics and Computation, 2022, vol. 430, issue C

Abstract: This paper studies the stability problem and H∞ performance of networked control system (NCS) in the presence of mixed attacks by developing an improved event-triggered mechanism (ETM). Firstly, both aperiodic denial of service (DoS) attacks and random deception attacks are encountered for investigating system dynamic behavior. Then, a resilient optimized dynamic event-triggered mechanism (RODETM) is proposed for reducing the unnecessary costs of system operation and mitigating the impact caused by attacks. On this basis, the standard NCS is reformulated into a switched system under the mixed attacks. Further, using the piecewise Lyapunov-Krasovskii functional method, average dwell time scheme and the linear matrix inequality (LMI) method, some sufficient conditions with control design implementation are obtained, which can ensure the exponential stability with the expected prescribed H∞ performance index of the studied system. Finally, the effectiveness of the proposed approach is demonstrated by using a numerical simulation with comparative analysis.

Keywords: Denial of service attacks; deception attacks; resilient optimized dynamic event-triggered mechanism; networked control system; exponential stability; H∞ performance (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300322003745
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:430:y:2022:i:c:s0096300322003745

DOI: 10.1016/j.amc.2022.127300

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:apmaco:v:430:y:2022:i:c:s0096300322003745