Adaptive event-triggered synchronization of neural networks under stochastic cyber-attacks with application to Chua’s circuit
This paper focuses on the synchronization control problem for neural networks (NNs) subject to stochastic cyber-attacks. Firstly, an adaptive event-triggered scheme (AETS) is adopted to improve the utilization rate of network resources, and an output feedback controller is constructed for improving...
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| Published in | Neural networks Vol. 166; pp. 11 - 21 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Elsevier Ltd
01.09.2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0893-6080 1879-2782 1879-2782 |
| DOI | 10.1016/j.neunet.2023.07.004 |
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| Abstract | This paper focuses on the synchronization control problem for neural networks (NNs) subject to stochastic cyber-attacks. Firstly, an adaptive event-triggered scheme (AETS) is adopted to improve the utilization rate of network resources, and an output feedback controller is constructed for improving the performance of the system subject to the conventional deception attack and accumulated dynamic cyber-attack. Secondly, the synchronization problem of master–slave NNs is transformed into the stability analysis problem of the synchronization error system. Thirdly, by constructing a customized Lyapunov–Krasovskii functional (LKF), the adaptive event-triggered output feedback controller is designed to ensure the synchronization error system is asymptotically stable with a given H∞ performance index. Lastly, in the simulation part, two examples, including Chua’s circuit, illustrate the feasibility and universality of the related technologies in this paper. |
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| AbstractList | This paper focuses on the synchronization control problem for neural networks (NNs) subject to stochastic cyber-attacks. Firstly, an adaptive event-triggered scheme (AETS) is adopted to improve the utilization rate of network resources, and an output feedback controller is constructed for improving the performance of the system subject to the conventional deception attack and accumulated dynamic cyber-attack. Secondly, the synchronization problem of master-slave NNs is transformed into the stability analysis problem of the synchronization error system. Thirdly, by constructing a customized Lyapunov-Krasovskii functional (LKF), the adaptive event-triggered output feedback controller is designed to ensure the synchronization error system is asymptotically stable with a given H
performance index. Lastly, in the simulation part, two examples, including Chua's circuit, illustrate the feasibility and universality of the related technologies in this paper. This paper focuses on the synchronization control problem for neural networks (NNs) subject to stochastic cyber-attacks. Firstly, an adaptive event-triggered scheme (AETS) is adopted to improve the utilization rate of network resources, and an output feedback controller is constructed for improving the performance of the system subject to the conventional deception attack and accumulated dynamic cyber-attack. Secondly, the synchronization problem of master–slave NNs is transformed into the stability analysis problem of the synchronization error system. Thirdly, by constructing a customized Lyapunov–Krasovskii functional (LKF), the adaptive event-triggered output feedback controller is designed to ensure the synchronization error system is asymptotically stable with a given H∞ performance index. Lastly, in the simulation part, two examples, including Chua’s circuit, illustrate the feasibility and universality of the related technologies in this paper. This paper focuses on the synchronization control problem for neural networks (NNs) subject to stochastic cyber-attacks. Firstly, an adaptive event-triggered scheme (AETS) is adopted to improve the utilization rate of network resources, and an output feedback controller is constructed for improving the performance of the system subject to the conventional deception attack and accumulated dynamic cyber-attack. Secondly, the synchronization problem of master-slave NNs is transformed into the stability analysis problem of the synchronization error system. Thirdly, by constructing a customized Lyapunov-Krasovskii functional (LKF), the adaptive event-triggered output feedback controller is designed to ensure the synchronization error system is asymptotically stable with a given H∞ performance index. Lastly, in the simulation part, two examples, including Chua's circuit, illustrate the feasibility and universality of the related technologies in this paper.This paper focuses on the synchronization control problem for neural networks (NNs) subject to stochastic cyber-attacks. Firstly, an adaptive event-triggered scheme (AETS) is adopted to improve the utilization rate of network resources, and an output feedback controller is constructed for improving the performance of the system subject to the conventional deception attack and accumulated dynamic cyber-attack. Secondly, the synchronization problem of master-slave NNs is transformed into the stability analysis problem of the synchronization error system. Thirdly, by constructing a customized Lyapunov-Krasovskii functional (LKF), the adaptive event-triggered output feedback controller is designed to ensure the synchronization error system is asymptotically stable with a given H∞ performance index. Lastly, in the simulation part, two examples, including Chua's circuit, illustrate the feasibility and universality of the related technologies in this paper. |
| Author | Xu, Yao Zhu, Song Ma, Lei Zhou, Linna Yang, Chunyu |
| Author_xml | – sequence: 1 givenname: Yao surname: Xu fullname: Xu, Yao email: yaoxu@cumt.edu.cn organization: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China – sequence: 2 givenname: Chunyu orcidid: 0000-0002-1590-1712 surname: Yang fullname: Yang, Chunyu email: chunyuyang@cumt.edu.cn organization: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China – sequence: 3 givenname: Linna orcidid: 0000-0003-2883-400X surname: Zhou fullname: Zhou, Linna email: linnazhou@cumt.edu.cn organization: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China – sequence: 4 givenname: Lei surname: Ma fullname: Ma, Lei email: maleinjust@126.com organization: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China – sequence: 5 givenname: Song surname: Zhu fullname: Zhu, Song email: songzhu@cumt.edu.cn organization: School of Mathematics, China University of Mining and Technology, Xuzhou, 221116, China |
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| Keywords | Chua’s circuit Stochastic cyber-attacks Neural networks Adaptive event-triggered scheme Synchronization control |
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| Snippet | This paper focuses on the synchronization control problem for neural networks (NNs) subject to stochastic cyber-attacks. Firstly, an adaptive event-triggered... |
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| SubjectTerms | Adaptive event-triggered scheme Chua’s circuit Neural networks Stochastic cyber-attacks Synchronization control |
| Title | Adaptive event-triggered synchronization of neural networks under stochastic cyber-attacks with application to Chua’s circuit |
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