This article addresses the secure finite-time tracking problem via event-triggered command-filtered control for nonlinear time-delay cyber physical systems(CPSs)subject to cyber attacks.Under the attack circumstance,t...This article addresses the secure finite-time tracking problem via event-triggered command-filtered control for nonlinear time-delay cyber physical systems(CPSs)subject to cyber attacks.Under the attack circumstance,the output and state information of CPSs is unavailable for the feedback design,and the classical coordinate conversion of the iterative process is incompetent in relation to the tracking task.To solve this,a new coordinate conversion is proposed by considering the attack gains and the reference signal simultaneously.By employing the transformed variables,a modified fractional-order command-filtered signal is incorporated to overcome the complexity explosion issue,and the Nussbaum function is used to tackle the varying attack gains.By systematically constructing the Lyapunov-Krasovskii functional,an adaptive event-triggered mechanism is presented in detail,with which the communication resources are greatly saved,and the finite-time tracking of CPSs under cyber attacks is guaranteed.Finally,an example demonstrates the effectiveness.展开更多
This paper considers the leader-following consensus for a class of nonlinear switched multi-agent systems(MASs)with non-strict feedback forms and input saturations under unknown switching mechanisms.First,in virtue of...This paper considers the leader-following consensus for a class of nonlinear switched multi-agent systems(MASs)with non-strict feedback forms and input saturations under unknown switching mechanisms.First,in virtue of Gaussian error functions,the saturation nonlinearities are represented by asymmetric saturation models.Second,neural networks are utilized to approximate some unknown packaged functions,and the structural property of Gaussian basis functions is introduced to handle the non-strict feedback terms.Third,by using the backstepping process,a common Lyapunov function is constructed for all the subsystems of the followers.At last,we propose an adaptive consensus protocol,under which the tracking error under arbitrary switching converges to a small neighborhood of the origin.The effectiveness of the proposed protocol is illustrated by a simulation example.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.62103199 and 62103201)the Natural Science Foundation of Jiangsu Province,China(No.BK20210590)the China Postdoctoral Science Foundation(Nos.2022M711690 and 2023T160333)。
文摘This article addresses the secure finite-time tracking problem via event-triggered command-filtered control for nonlinear time-delay cyber physical systems(CPSs)subject to cyber attacks.Under the attack circumstance,the output and state information of CPSs is unavailable for the feedback design,and the classical coordinate conversion of the iterative process is incompetent in relation to the tracking task.To solve this,a new coordinate conversion is proposed by considering the attack gains and the reference signal simultaneously.By employing the transformed variables,a modified fractional-order command-filtered signal is incorporated to overcome the complexity explosion issue,and the Nussbaum function is used to tackle the varying attack gains.By systematically constructing the Lyapunov-Krasovskii functional,an adaptive event-triggered mechanism is presented in detail,with which the communication resources are greatly saved,and the finite-time tracking of CPSs under cyber attacks is guaranteed.Finally,an example demonstrates the effectiveness.
基金supported in part by the National Key Research and Development Program(2018YFA0702202)in part by the Leadingedge Technology Program of Jiangsu National Science Foundation(BK20202011)in part by the Research Grants of the Nanjing University of Posts and Telecommunications(NY220158,NY220177)。
文摘This paper considers the leader-following consensus for a class of nonlinear switched multi-agent systems(MASs)with non-strict feedback forms and input saturations under unknown switching mechanisms.First,in virtue of Gaussian error functions,the saturation nonlinearities are represented by asymmetric saturation models.Second,neural networks are utilized to approximate some unknown packaged functions,and the structural property of Gaussian basis functions is introduced to handle the non-strict feedback terms.Third,by using the backstepping process,a common Lyapunov function is constructed for all the subsystems of the followers.At last,we propose an adaptive consensus protocol,under which the tracking error under arbitrary switching converges to a small neighborhood of the origin.The effectiveness of the proposed protocol is illustrated by a simulation example.
