Status | 已发表Published |
Title | Neural network-based control for RRP-based networked systems under DoS attacks with power interval |
Creator | |
Date Issued | 2022-11-01 |
Source Publication | Automatica
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ISSN | 0005-1098 |
Volume | 145 |
Abstract | This paper is concerned with the optimal control problem for networked systems with the round-robin protocol (RRP) under the denial-of-service (DoS) attacker with power interval. In the literature, the control design is studied for the linear networked system subject to the DoS attacks with a known constant power or a known constant probability of data-packet dropouts. In this paper, the objective is to control the unknown nonlinear system in the communication network subject to the DoS attacks with a power interval and a time-varying probability of data-packet dropouts. The effects of the DoS attacks with power interval on a networked system under RRP are modeled accurately. A neural network (NN) -based observer is designed for the nonlinear system under the DoS attacks with power interval, and the relationship between the DoS attacker power interval and state estimation error is obtained. The NN actor–critic policy for the optimal control of the RRP-based networked system under the DoS attacks with power interval is found with adaptive dynamical programming, and stability of the resulting control system is analyzed. The proposed control method is demonstrated by a networked uninterruptible power supply system. |
Keyword | Critic–actor structure DoS attacks Neural network-based control Power interval Round-robin protocol |
DOI | 10.1016/j.automatica.2022.110555 |
URL | View source |
Indexed By | SCIE |
Language | 英语English |
WOS Research Area | Automation & Control Systems ; Engineering |
WOS Subject | Automation & Control Systems ; Engineering, Electrical & Electronic |
WOS ID | WOS:000863176200008 |
Scopus ID | 2-s2.0-85137616147 |
Citation statistics | |
Document Type | Journal article |
Identifier | http://repository.uic.edu.cn/handle/39GCC9TT/10151 |
Collection | Faculty of Science and Technology |
Corresponding Author | Sun, Jitao |
Affiliation | 1.School of Mathematical Sciences,Tongji University,Shanghai,200092,China 2.Institute of Artificial Intelligence and Future Networks,Beijing Normal University at Zhuhai,Zhuhai,519087,China 3.Guangdong Key Lab of AI and Multi-Modal Data Processing,BNU-HKBU United International College,Zhuhai,519087,China 4.Institute for Intelligent Systems,Faculty of Engineering and the Built Environment,University of Johannesburg,Johannesburg,South Africa |
Recommended Citation GB/T 7714 | Zhang, Junhui,Wang, Qingguo,Marwala, Tshilidziet al. Neural network-based control for RRP-based networked systems under DoS attacks with power interval[J]. Automatica, 2022, 145. |
APA | Zhang, Junhui, Wang, Qingguo, Marwala, Tshilidzi, & Sun, Jitao. (2022). Neural network-based control for RRP-based networked systems under DoS attacks with power interval. Automatica, 145. |
MLA | Zhang, Junhui,et al."Neural network-based control for RRP-based networked systems under DoS attacks with power interval". Automatica 145(2022). |
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