Resilient fuzzy stabilization is capable of providing much less conservative results than conventional fuzzy stabilization while the alert threshold condition should be always satisfied at each sampling instant. In order to make the alert threshold condition more easily to be guaranteed, the short paper employs the switching-type gain-scheduling control law so that the real-time information which is specific to the current sampling instant can be integrated into resilient fuzzy stabilization. More importantly, a new kind of time-variant balanced matrix is introduced for the first time for adjusting positive/negative terms of different monomials in a more flexible way. As a result, the conservatism of resilient fuzzy stabilization can be further reduced even if the alert threshold condition becomes more difficult to be violated. Finally, the advantage of the developed method is tested and validated via related comparisons on a benchmark example.

This paper focuses on the issue of designing an adaptive event-triggered scheme to the decentralized filtering for a class of networked nonlinear interconnected system. A novel adaptive event-triggered condition is proposed by constructing an adaptive law for the threshold. This new type of threshold mainly depends on the error between the states at the current sampling instant and the latest releasing instant, by which the data release rate is adapted to the variation of the system. The limitation of network bandwidth is alleviated on account of a large amount of ``unnecessary'' packets being dropped out before accessing the network. Sufficient conditions are derived such that the overall filtering error system under the proposed adaptive data-transmitting scheme is asymptotically stable with a prescribed disturbance attenuation level. An example is given to show the effectiveness of the proposed scheme.

This article focuses on the problem of resilient H∞ filtering for Takagi-Sugeno fuzzy-model-based nonlinear networked systems with multisensors. A weighted fusion approach is adopted before information from multisensors is transmitted over the network. A novel event-triggered mechanism is proposed, which allows us not only to reduce the data-releasing rate but also to prevent abnormal data being potentially transmitted over the network due to sensor measurement or other practical factors. The problem of denial-of-service (DoS) attacks, which often occurs in a communication network, is also considered, where the DoS attack model is based on an assumption that the periodic attack includes active periods and sleeping periods. By employing the idea of the switching model for filtering error systems to deal with DoS attacks, sufficient conditions are derived to guarantee that the filtering error system is exponentially stable. Simulation results are given to demonstrate the effectiveness of the theoretical analysis and design method.

This article studies the weighted memory-event-triggered $H_{\infty}$ static output control issue of Takagi–Sugeno fuzzy wind turbine systems with uncertainty. To decrease the frequency of data communication, a novel adaptive memory-event-triggered mechanism is presented to choose the “necessary” control signals, which has the following two benefits. First, a weighted average signal over a historic period is utilized as the input of event-triggered scheme, instead of the current system information in the conventional one. This could reduce the control signal updating rate and avoid the false triggering events incurred by stochastic environment noises and disturbances. Second, a dynamic triggering threshold is adopted to adaptively regulate the control signal updating frequency along with the average signal. By applying the distributed delay system method to describe the weighted historic signal, a new uncertain T–S fuzzy wind turbine system with distributed delay is established. With the aid of the measured outputs and the integral inequality based on the weighting function of the average signal, the memory-event-triggered static output controller design conditions are obtained to ensure the system exponential stability and the $H_{\infty}$ performance. Lastly, an experiment platform integrating Zigbee modules as the wireless network is set up to illustrate the advantages of the proposed strategy.

This paper investigates the problem of resilient control for the T-S fuzzy systems against bounded cyber-attack. A novel memory-based event triggering mechanism (ETM) is developed, by which the past information of the physical process through the window function is utilized. Using such an ETM can not only lead to a lower data-releasing rate but also reduce the occurrence of wrong triggering event. Furthermore, the frequency of event generation is relatively smoother than existing ETMs. From the current releasing instant to the next, two periods are designed. The ETM works only when the first period ends, thereby avoiding the Zeno behavior that commonly exists in continuous ETM designs. The control system is then formulated as a switched fuzzy control system with two modes in each releasing period. Based on an assumption of secure control and the proposed ETM, sufficient conditions are obtained to guarantee the exponential stability of networked T-S fuzzy systems in the presence of deception attacks in secure sense. Finally, a single-link rigid robot is taken as an example to illustrate the advantages of theoretical results.

This article investigates the problem of resilient secure control of cloud-aided 5-DOF active semivehicle suspension systems (SVSSs). A novel joint model considering both the event-triggered mechanism (ETM) and Denial of Service (DoS) attacks is established. Under such a model, during the active period of DoS attacks, periodic transmission attempt is made to ensure the control system can receive the control information at the earliest time; the ETM turns to be a conventional one when the DoS attack is in sleeping period. Meanwhile, the valid attack period is proposed to address the problem of the DoS attack ending within a sampling period, which is a challenging problem in modeling DoS attacks. Takagi–Sugeno (T–S) fuzzy model is used to characterize the uncertainties of sprung and unsprung mass of SVSSs. By converting the cloud-aided active SVSS into a fuzzy-based switched time-delay system, and using the method of piecewise Lyapunov function, sufficient conditions are derived to ensure the performances of active SVSSs subject to DoS attacks. Finally, the effectiveness of the proposed method is validated by a numerical example of active SVSSs subject to DoS attacks.