Robust Resilient Control for Nonlinear Systems Under Denial-of-Service Attacks

This article is concerned with the design of robust resilient control strategy for nonlinear systems under Denial-of-Service (DoS) attacks. First, Takagi–Sugeno fuzzy model is employed to approximate the nonlinear dynamics, and an improved sensor system is constructed by fuzzy observer and fuzzy predictor. By applying periodic event-triggered control strategy, the relationship between the estimated state and predicted state is obtained by event-triggering mechanism, which can reduce transmission attempts significantly in the sensor-to-controller channel. Second, caused by DoS attacks, the transmission attempts may be denied over the communication network. Under the proposed transmission policy with a bounded update period, input-to-state stability (ISS) of closed-loop systems can be guaranteed. Moreover, the maximum frequency and duration of DoS attacks are calculated. Finally, simulation results are provided to show the effectiveness of the proposed method.

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Robust Resilient Control for Nonlinear Systems Under Denial-of-Service Attacks

Semantic Scholar · Computer Science · 2021

Abstract

This article is concerned with the design of robust resilient control strategy for nonlinear systems under Denial-of-Service (DoS) attacks. First, Takagi–Sugeno fuzzy model is employed to approximate the nonlinear dynamics, and an improved sensor system is constructed by fuzzy observer and fuzzy predictor. By applying periodic event-triggered control strategy, the relationship between the estimated state and predicted state is obtained by event-triggering mechanism, which can reduce transmission attempts significantly in the sensor-to-controller channel. Second, caused by DoS attacks, the transmission attempts may be denied over the communication network. Under the proposed transmission policy with a bounded update period, input-to-state stability (ISS) of closed-loop systems can be guaranteed. Moreover, the maximum frequency and duration of DoS attacks are calculated. Finally, simulation results are provided to show the effectiveness of the proposed method.

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