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This article centers around the privacy‐preserving‐based secure H∞$$ {H}_{\infty } $$ filtering issue for interval type‐2 (IT‐2) fuzzy networked systems with false data injection (FDI) attacks. In order to achieve the goal of privacy preserving and significantly enhancing system security against potential eavesdropping threats, a novel encryption‐decryption mechanism (EDM) is adopted to safeguard the safety of signals across the network. The mechanism encrypts the transmitted signal by introducing artificial noise, secret key, and utilizing randomly selected nodes. This ensures that the actual transmitted data remains invisible to eavesdroppers while minimally the impact on the estimated performance of the proposed EDM. Given the network communication resources are becoming constrained due to the ever‐increasing network traffic, an adaptive event‐triggered mechanism (AETM) is employed to ease network congestion by an adaptively adjustable threshold. Then, various sufficient conditions have been outlined to ensure that the filtering error system meets the prescribed disturbance attenuation level. In the end, a numerical example is presented to evaluate both the precision and effectiveness of the developed algorithms. [ABSTRACT FROM AUTHOR]

The article concentrates on exploring the issue of privacy‐preserving sliding mode consensus of multi‐agent systems (MASs) with disturbance. An encryption and decryption algorithm has been proposed to address data security and privacy issues during data transmission. To optimize network resource allocation, a dynamic event‐triggering mechanism has been introduced, which reduces the number of encrypted data while saving the computation cost. The consensus performance based on the sliding mode control strategy is achieved when the reachability of the slide‐mode surface is guaranteed, and then the slide‐mode controller is developed. Finally, an empirical demonstration through a numerical example validates the efficacy of the proposed strategy. [ABSTRACT FROM AUTHOR]

In this study, the security quantized control problem is investigated for discrete‐time Takagi‐Sugeno (T‐S) fuzzy systems with deception attacks based on the multi‐channel‐enabled round‐robin (MCERR) protocol. The MCERR protocol breaks through the limitation in the well‐known RR protocol where only one signal can be transmitted at every turn. Under MCERR protocol, multiple transmission channels are put to use and a set of sensor nodes can gain access to network. Considering the random deception attacks and the measurement outliers, a new system model is established and a sufficient condition is derived to ensure the stability of the discussed system. Furthermore, an outlier resistant observer‐based controller which can mitigate the impact of deception attacks is developed. Besides, the concrete expressions of observer gains and controller gains are obtained. Finally, the effectiveness of the proposed method can be validated by simulation results. [ABSTRACT FROM AUTHOR]

This article considers the issue of finite‐time H∞ asynchronous state estimation for event‐triggered nonlinear Markovian jump systems subject to cyber‐attacks. An adaptive event‐triggered scheme is introduced to cope with the capacity constraint of the networked resources. It is assumed that the transmitted sensor measurements may experience randomly malicious cyber‐attacks. Considering the effect of the adaptive event‐triggered scheme and the occurrence of cyber‐attacks, we establish a new state estimation error system model. Sufficient conditions of the finite‐time boundedness and the H∞ finite‐time boundedness are developed for the augmented system. Then, the design methods of the asynchronous estimator gains are derived, which can ensure the H∞ finite‐time boundedness of the estimation error system. Finally, a numerical example is given to show the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

In this article, the event‐triggered data‐driven consensus problem is studied for multi‐agent systems (MASs) with switching topologies under denial‐of‐service (DoS) attacks. Based on the model‐free adaptive control (MFAC) approach, the controller is only correlated with the input/output (I/O) data of agents instead of the specific system model. First, the pseudo partial derivative (PPD) is employed to dynamically linearize the system model. Second, to save network bandwidth, an event‐triggered scheme is introduced according to the I/O measurement and the output estimated error. Third, an attack compensation mechanism is adopted for the purpose of reducing the influence of DoS attacks. Then, a data‐driven controller is designed to make the agents approach the desired trajectory on the basis of the estimation value of PPD. Moreover, by utilizing the Lyapunov stability theory, the tracking error is demonstrated to be convergent and the reliability of the controller is investigated. Finally, an example is simulated to verify the effectiveness of the consensus tracking strategy. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with security distributed state estimation for nonlinear networked systems against denial‐of‐service attacks. By taking the effects of resource constraints into consideration, an event‐triggered scheme and a quantization mechanism are employed to alleviate the burden of network. A mathematical model of distributed state estimation is constructed for nonlinear networked systems against denial‐of‐service attacks. Sufficient conditions ensuring the exponential stability of the estimation error systems are obtained by utilizing the Lyapunov stability theory. The explicit expressions of the designed state estimators are acquired in terms of the linear matrix inequalities. Finally, a numerical example is used to testify the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the resilient observer-based output feedback controller is designed for a class of networked T–S fuzzy systems under a hybrid-triggered scheme and mismatched membership functions. In order to improve network bandwidth utilization, a hybrid-triggered scheme is introduced between the state observer and the controller, which is based on a switching between periodic sampling and an event-triggered scheme. Considering the inaccurate implementation of the parameters of the observer-based controller, a novel hybrid-triggered T–S fuzzy model is constructed. Sufficient conditions are established for the augmented fuzzy systems by using Lyapunov theory and the linear matrix inequality techniques. Furthermore, the observer-based controller gains are designed in terms of linear matrix inequalities. Finally, a numerical example is provided to demonstrate the usefulness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is concerned with H ∞ output feedback control of event-triggered Markovian jump systems with measured output quantizations. An event-triggered mechanism and a quantization scheme are designed to reduce the occupancy of the limited network resources. The measured output is directly transmitted to the event generator, whether the released signal can be sent out to the controller through the quantizer depends on the triggering condition. A new Markovian jump time-delay system model with external disturbances is then presented and sufficient conditions are derived to guarantee the stability of the resulting closed-loop system and prescribed performance. Criteria for co-designing both the output feedback gain and the trigger parameters are established. Finally, a numerical example confirms the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]