This article investigates the problem of observer-based switching-like event-triggered control (ETC) for non- linear networked systems subject to aperiodic denial-of-service (DoS) attacks. First, a full-order state observer is developed to estimate the unavailable system states and used to establish the switching-like event-triggered condition, which includes two different threshold para- meters. Second, in order to improve the bandwidth re- source utilization and compensate for the influence of DoS attacks, a switching-like event-triggered mechanism (SETM) is designed, which can adaptively switch two different threshold parameters based on the presence or absence of DoS attacks. By combining the proposed SETM, an output feedback controller is constructed and a new observer-based switching-like ETC strategy is presented for nonlinear networked systems. Meanwhile, the relationship between the inactive/active period of the DoS attacks, the parameters of the SETM, the unmeasurable states, and the sampling period in the model are quanti- tatively discussed on the basis of the new strategy. Then, in terms of the proposed control strategy, the global asymptotical stability of the nonlinear networked systems can be obtained. Finally, two examples are used to verify the feasibility and effectiveness of the designed strategy.

This paper investigates the problem of predictor-based decentralized event-triggered secure control for nonlinear cyber-physical systems (CPSs) subject to replay attacks and time delay. To overcome the limitation of the network bandwidth, a periodic decentralized event-triggered scheme (PDETS) is designed for non-strict feedback nonlinear CPSs in the presence of replay attacks. Then, decentralized output feedback controllers are constructed by designing predictor-based observers to attenuate the influences of replay attacks and time delay. Based on the proposed new framework, the global exponential stability (GES) of the resulting nonlinear CPSs can be guaranteed. Finally, two application examples verify the effectiveness of the proposed method.

This paper investigates the estimate-based adaptive neural secure control method for nonminimum-phase nonlinear networked control systems (NNCSs) under hybrid attacks via dynamic event-triggered scheme. Hybrid attacks such as denial-of-service (DoS) attacks and false data injection (FDI) attacks are assumed to occur in the sensor-to-controller (STC) channel and controller-to-actuator (CTA) channel. When only the system output is obtained, a sampled-data observer is introduced to estimate unknown system states. In order to improve the utilization of communication bandwidth under DoS attacks, a dynamic event-triggered scheme (DETS) is proposed to save network resources. An event-triggered output feedback controller is designed by utilizing neural network (NN) to approximate FDI signals. Based on the proposed dynamic event-triggered control strategy, the selections of the sampling period and the observer gain are derived to ensure the boundedness of the control systems. At last, the efficiency of the control strategy is verified by a numerical example.