Stabilization of stochastic complex networks with switching jump diffusions based on adaptive aperiodically intermittent control

Liu, Yan; Chu, Dianhui; Zou, Yaxuan; Su, Huan

doi:10.1007/s11071-021-06467-3

Cited by 9 publications

(2 citation statements)

References 39 publications

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“…However, with the development of networks, the heterogeneous network is one of our future research directions. Meanwhile, the stochastic model [50] and fractional order model [51] are also the trends in our future research.…”

Section: Discussionmentioning

confidence: 98%

Analysis and Control of Malware Mutation Model in Wireless Rechargeable Sensor Network with Charging Delay

et al. 2022

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In wireless rechargeable sensors (WRSNs), the system is vulnerable to be attacked by malware. Because of the distributed network structure of WRSNs, the malware attack has great influence on the security system of WRSNs. With the variability in malware, the problem of decryption and coding errors will lead to the malware mutating. In this paper, there are two problems to be solved, including the malware mutation and the charging delay in WRSNs. The malware mutation state and the low-energy state are introduced. Firstly, three different equilibrium solutions of the mutation model are given. Then, the local stability is proven by the characteristic equation, and the system will be stabilized at different equilibrium solutions when the base reproductive number is different. With the condition of charging delay, the bifurcation phenomenon is investigated by using the Hopf bifurcation theory. Furthermore, to improve the security of WRSNs and decrease the control cost, the Pontryagin’s Maximum principle is applied to obtain an optimal control scheme under mutation and charging delay. Finally, the numerical simulation is applied by Matlab to confirm this model. The simulation results show that the mutation malware can be controlled when the delay is less than the maximum threshold.

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Section: Discussionmentioning

confidence: 98%

Analysis and Control of Malware Mutation Model in Wireless Rechargeable Sensor Network with Charging Delay

et al. 2022

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“…Stabilization is an essential control problem. There are abundant results related to the stabilization of various dynamical models like linear systems (Brockett and Liberzon, 2000), non-linear systems (Mirzaei et al, 2021), and networked systems (Liu et al, 2021). Meanwhile, different control methods, such as output feedback (Jia et al, 2020) and event-triggered strategies (Peng and Ai, 2019), have also been proposed to implement the stabilization of dynamical systems.…”

Section: Introductionmentioning

confidence: 99%

The feedback stabilization of finite-state fuzzy cognitive maps

Xiaojie

Luo

2022

Transactions of the Institute of Measurement and Control

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Fuzzy cognitive maps (FCMs) are a kind of cognitive model for knowledge representation and causal inference. Meanwhile, as fuzzy dynamical systems, FCMs have also been widely applied in the control-related fields, such as mobile robots, unmanned aerial vehicles (UAVs), and industrial controls. However, the existing works mainly focused on the practical applications but lacked the necessary theoretical discussions related to the FCM-based control mechanism. As is known, stabilization is one of the fundamental issues in the control fields. Till date, rigorous research on the stabilization of FCMs is still an issue to be studied. In this article, using state feedback control method, the global stabilizations of finite-state FCMs are investigated. First, utilizing the semi-tensor product (STP) of matrices, the algebraic expression of FCM can be derived. Some theorems ensure the sufficient condition for the existence of the state feedback controller of the global stabilization. Second, the constructive design processes of state feedback controllers are discussed in detail. Third, the global stabilization is further extended into partial stabilization, where only specific concepts of FCMs can be stabilized. The corresponding theoretical analysis is implemented. Finally, the effectiveness of the proposed methods is verified by several examples.

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Periodic self-triggered intermittent sampled-data stabilization for stochastic complex networks

et al. 2022

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Stabilization of stochastic complex networks with switching jump diffusions based on adaptive aperiodically intermittent control

Cited by 9 publications

References 39 publications

Analysis and Control of Malware Mutation Model in Wireless Rechargeable Sensor Network with Charging Delay

Analysis and Control of Malware Mutation Model in Wireless Rechargeable Sensor Network with Charging Delay

The feedback stabilization of finite-state fuzzy cognitive maps

Periodic self-triggered intermittent sampled-data stabilization for stochastic complex networks

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