This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-tri...This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.展开更多
In this paper, incorporating memory-based diffusion and delay, we propose a partly diffusive plant–pollinator model under Neumann boundary condition. Then, we investigate the effects of memory-based diffusion and del...In this paper, incorporating memory-based diffusion and delay, we propose a partly diffusive plant–pollinator model under Neumann boundary condition. Then, we investigate the effects of memory-based diffusion and delay on the dynamics of this model through discussing the corresponding characteristic equation. And we find that Turing bifurcations and Hopf bifurcations can be induced by memory-based diffusion and delay, respectively. By performing some numerical simulations, stable spatially homogeneous periodic solutions and inhomogeneous steady state solutions are obtained, which illustrates and expands our results in this paper. Moreover, the unstable spatially inhomogeneous periodic solutions occur only for some time, then they eventually converge to a spatially homogeneous periodic solutions.展开更多
In this article,we study the secure control of the Markovian jumping neural networks(MJNNs)subject to deception attacks.Considering the limitation of the network bandwidth and the impact of the deception attacks,we pr...In this article,we study the secure control of the Markovian jumping neural networks(MJNNs)subject to deception attacks.Considering the limitation of the network bandwidth and the impact of the deception attacks,we propose two memory-based adaptive event-trigger mechanisms(AETMs).Different from the available event-trigger mechanisms,these two memory-based AETMs contain the historical triggered data not only in the triggering conditions,but also in the adaptive law.They can adjust the data transmission rate adaptively so as to alleviate the impact of deception attacks on the controlled system and to suppress the peak of the system response.In view of the proposed memory-based AETMs,a time-dependent Lyapunov functional is constructed to analyze the stability of the error system.Some sufficient conditions to ensure the asymptotical synchronization of master-slave MJNNs are obtained,and two easy-to-implement co-design algorithms for the feedback gain matrix and the trigger matrix are given.Finally,a numerical example is given to verify the feasibility and superiority of the two memory-based AETMs.展开更多
This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method...This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method is employed to achieve secure control by estimating the system's state in real time.Secondly,by combining a memory-based adaptive eventtriggered mechanism with neural networks,the paper aims to approximate the nonlinear terms in the networked system and efficiently conserve system resources.Finally,based on a two-degree-of-freedom model of a vehicle affected by crosswinds,this paper constructs a multi-unmanned ground vehicle(Multi-UGV)system to validate the effectiveness of the proposed method.Simulation results show that the proposed control strategy can effectively handle external disturbances such as crosswinds in practical applications,ensuring the stability and reliable operation of the Multi-UGV system.展开更多
The problem of flapping motion control of Micro Air Vehicles (MAVs) with flapping wings was studied in this paper.Based upon the knowledge of skeletal and muscular components of hummingbird, a dynamic model for flappi...The problem of flapping motion control of Micro Air Vehicles (MAVs) with flapping wings was studied in this paper.Based upon the knowledge of skeletal and muscular components of hummingbird, a dynamic model for flapping wing wasdeveloped.A control scheme inspired by human memory and learning concept was constructed for wing motion control ofMAVs.The salient feature of the proposed control lies in its capabilities to improve the control performance by learning fromexperience and observation on its current and past behaviors, without the need for system dynamic information.Furthermore,the overall control scheme has a fairly simple structure and demands little online computations, making it attractive for real-timeimplementation on MAVs.Both theoretical analysis and computer simulation confirms its effectiveness.展开更多
文摘This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.
基金supported by the National Natural Science Foundation of China(Nos.12261050 and 62062042)Science and Technology Project of Department of Education of Jiangxi Province(Nos.GJJ2201612 and GJJ201015).
文摘In this paper, incorporating memory-based diffusion and delay, we propose a partly diffusive plant–pollinator model under Neumann boundary condition. Then, we investigate the effects of memory-based diffusion and delay on the dynamics of this model through discussing the corresponding characteristic equation. And we find that Turing bifurcations and Hopf bifurcations can be induced by memory-based diffusion and delay, respectively. By performing some numerical simulations, stable spatially homogeneous periodic solutions and inhomogeneous steady state solutions are obtained, which illustrates and expands our results in this paper. Moreover, the unstable spatially inhomogeneous periodic solutions occur only for some time, then they eventually converge to a spatially homogeneous periodic solutions.
基金supported by the National Natural Science Foundation of China (Grant Nos.61973199,62003794,and 62173214)the Shandong Provincial Natural Science Foundation (Grant Nos.ZR2020QF050 and ZR2021MF003)the Taishan Scholar Project of Shandong Province of China。
文摘In this article,we study the secure control of the Markovian jumping neural networks(MJNNs)subject to deception attacks.Considering the limitation of the network bandwidth and the impact of the deception attacks,we propose two memory-based adaptive event-trigger mechanisms(AETMs).Different from the available event-trigger mechanisms,these two memory-based AETMs contain the historical triggered data not only in the triggering conditions,but also in the adaptive law.They can adjust the data transmission rate adaptively so as to alleviate the impact of deception attacks on the controlled system and to suppress the peak of the system response.In view of the proposed memory-based AETMs,a time-dependent Lyapunov functional is constructed to analyze the stability of the error system.Some sufficient conditions to ensure the asymptotical synchronization of master-slave MJNNs are obtained,and two easy-to-implement co-design algorithms for the feedback gain matrix and the trigger matrix are given.Finally,a numerical example is given to verify the feasibility and superiority of the two memory-based AETMs.
基金The National Natural Science Foundation of China(W2431048)The Science and Technology Research Program of Chongqing Municipal Education Commission,China(KJZDK202300807)The Chongqing Natural Science Foundation,China(CSTB2024NSCQQCXMX0052).
文摘This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method is employed to achieve secure control by estimating the system's state in real time.Secondly,by combining a memory-based adaptive eventtriggered mechanism with neural networks,the paper aims to approximate the nonlinear terms in the networked system and efficiently conserve system resources.Finally,based on a two-degree-of-freedom model of a vehicle affected by crosswinds,this paper constructs a multi-unmanned ground vehicle(Multi-UGV)system to validate the effectiveness of the proposed method.Simulation results show that the proposed control strategy can effectively handle external disturbances such as crosswinds in practical applications,ensuring the stability and reliable operation of the Multi-UGV system.
文摘The problem of flapping motion control of Micro Air Vehicles (MAVs) with flapping wings was studied in this paper.Based upon the knowledge of skeletal and muscular components of hummingbird, a dynamic model for flapping wing wasdeveloped.A control scheme inspired by human memory and learning concept was constructed for wing motion control ofMAVs.The salient feature of the proposed control lies in its capabilities to improve the control performance by learning fromexperience and observation on its current and past behaviors, without the need for system dynamic information.Furthermore,the overall control scheme has a fairly simple structure and demands little online computations, making it attractive for real-timeimplementation on MAVs.Both theoretical analysis and computer simulation confirms its effectiveness.
