Event‐triggered quantized L2−L∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ filtering for neural networks under denial‐of‐service attacks

Abstract

This article deals with the reliable event‐triggered quantized frakturL2prefix−frakturL∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ filtering issue for neural networks with exterior interference under denial‐of‐service attacks. In order to lighten the load of communication channels and save network resources, a resilient event‐triggered mechanism and a quantization scheme are employed, simultaneously. By applying a piecewise Lyapunov–Krasovskii functional method, sufficient conditions containing limitations of denial‐of‐service attacks are derived to guarantee that the filter error system is exponentially stable as well as possesses a prescribed frakturL2prefix−frakturL∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ disturbance attenuation performance. Then, a co‐design method of the desired quantized frakturL2prefix−frakturL∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ filtering gain matrix and event‐triggering parameter can be obtained provided that the linear matrix inequalities have a feasible solution. Finally, the usefulness of the proposed design method is demonstrated by a numerical example.

Dynamic event‐triggered fault‐tolerant control through a new intermediate observer

“…Inspired by Reference 2, interesting results for different ET mechanisms (ETMs) were obtained, just to mention a few. [3][4][5][6][7][8][9][10][11][12][13][14][15][16] Specifically, a switching triggering rule was applied in Reference 3 to obtain a fixed inter-event time between two released instants. In Reference 4, an ET implementation was constructed for nonlinear systems using a hybrid system presentation.…”

Event‐triggered nonfragile state estimation for delayed neural networks with additive and multiplicative gain variations

“…[14][15][16][17] Such a triggering mechanism is easy to implement; however, when limited resources become a concern, it is highly preferable to bypass unnecessary signal transfers as long as satisfactory network performance is ensured. [18][19][20] In this scenario, incorporating a newly developed control mechanism called an event-triggered mechanism (ETM) into the state estimation issue will result in considerable energy savings. The main advantage of event-based state estimation is that it can significantly minimize communication resources while maintaining the expected estimation performance.…”

“…It is well noticed that in almost all results mentioned above, the state estimator for NNs has been designed using the classical time‐triggered sampling schemes; that is, measurement outputs are sampled at a sequence of periodic time instants 14‐17 . Such a triggering mechanism is easy to implement; however, when limited resources become a concern, it is highly preferable to bypass unnecessary signal transfers as long as satisfactory network performance is ensured 18‐20 . In this scenario, incorporating a newly developed control mechanism called an event‐triggered mechanism (ETM) into the state estimation issue will result in considerable energy savings.…”

Following Consistency of Energy‐Saving Operation for Urban Rail Trains Based on Event Triggering Mechanism

“…Li et al [19] proposed an event trigger strategy to reduce the communication burden of the two channels from the device and model to the controller. Zhou and Chang [20] applied an elastic trigger mechanism to reduce the communication channel load and save network resources.…”

“…In this kind of problem, the leader is not afected by other followers, and under the action of consistency agreement, a negotiation variable changes with the leader [21][22][23]. Te works [11][12][13][14][15][16][17][18][19][20][21][22][23] have studied the application of event-triggering mechanism and consistency protocol in other felds, which provides a reference for this study.…”