This paper analyzes the mechanism of denial-of-service (DoS) attacks initiated by hackers from the perspective of computer networks. In order to effectively estimate the performance error generated by the T-S fuzzy networked control systems (NCSs) under DoS attacks, we transform the performance error estimation (PEE) problem into the one of finding ellipsoid constraints $\mathfrak {J}(P_{i})$. First, improved Lyapunov-Krasovskii functions (LKFs) based on fuzzy membership functions (FMFs) are constructed, which combine the characteristics of nonlinear problems in the system to reduce the initial constraints. Then, a second-order weight method (SOWM) is introduced to divide the time interval of sampling meticulously. Besides, the information stored in the LKFs is enhanced. Furthermore, we construct the novel looped functions by relying on the SOWM. Next, a suitable integral elastic event trigger mechanism (EIETM) is established to ensure that the performance errors caused by the attacks are estimated. Finally, the feasibility of the proposed method is verified by a two-degree-of-freedom helicopter system (2-DoF HS).

This article examines the mechanisms by which aperiodic denial-of-service (DoS) attacks can exploit vulnerabilities in the TCP/IP transport protocol and its three-way handshake during communication data transmission to hack and cause data loss in networked control systems (NCSs). Such data loss caused by DoS attacks can eventually lead to system performance degradation and impose network resource constraints on the system. Therefore, estimating system performance degradation is of practical importance. By formulating the problem as an ellipsoid-constrained performance error estimation (PEE) problem, we can estimate the system performance degradation caused by DoS attacks. We propose a new Lyapunov–Krasovskii function (LKF) using the fractional weight segmentation method (FWSM) to examine the sampling interval and introduce a relaxed, positive definite constraint to optimize the control algorithm. We also propose a relaxed, positive definite constraint that reduces the initial constraints to optimize the control algorithm. Next, we introduce an alternate direction algorithm (ADA) to solve the optimal trigger threshold and design an integral-based event-triggered controller (IETC) to estimate the error performance of NCSs with limited network resources. Finally, we verify the effectiveness and feasibility of the proposed method using the Simulink joint platform autonomous ground vehicle (AGV) model.

This article investigates the stability problem of Takagi–Sugeno fuzzy networked control systems (TSNCSs) under deception cyberattacks via a reliable sampling mechanism, which has important research value for applications in network security. First, a fuzzy weight functional method is introduced, and a new Lyapunov–Krasovskii functional is developed, which better incorporates nonlinear problems in the model. Then, in order to reduce the initial constraints, improved time delay closed-loop functions are constructed that consider the delay information and the characteristics of the sampling time points. Furthermore, considering the reliability issues of controllers in real industry, we establish some sufficient conditions and implement a novel reliable sampling controller with deception attacks (DAs) to control the asymptotic stability of TSNCS. Finally, the correctness and feasibility of the proposed method are verified experimentally using an inverted pendulum system.

This paper focuses on the event-triggered strategy design of a two-degree-of-freedom (DoF) helicopter system (HS) with denial-of-service (DoS) attacks, which has essential applications in traffic information security and military information security. First, the attack characteristics of DoS are introduced from the cloud servers and converters at the physical layer. Then, hackers launching a DoS attack on HS also are considered. Second, a new first-order weight sampling (FOWS) control method is developed, fully considering sampling intervals resource consumption. Meanwhile, novel looped-functionals are constructed, which contain more sampling time information and sampling interval weight information. In addition, quadratic scaling is used to process the integral terms to obtain a tighter upper limit, which helps optimize the two control algorithms (TCAs). Furthermore, TCAs are obtained using the linear convex combination method (LCCM). Then, a new event-triggered controller under DoS attacks is designed to ensure the 2-DoF HS is asymptotically stable. Finally, the feasibility and superiority of our designed approach are verified through an experimental simulation.