This paper investigates the exponential synchronization of reaction-diffusion systems with communication delays and non-collocated sensor-actuator deployments. To mitigate the communication resource wastage inherent in traditional continuous-time control, a dwell-time-based event-triggered scheme is proposed, which effectively reduces the frequency of control signal updates. A limited number of sensors are spatially deployed to measure local average signals, and only valuable data are transmitted through the proposed event-triggered mechanism. To address communication delays induced by bandwidth constraints and locally distributed actuators, a spatiotemporal-dependent switching system is constructed. Subsequently, sufficient conditions for ensuring exponential synchronization are derived by constructing appropriate Lyapunov functionals that accommodate both collocated and non-collocated sensor-actuator configurations. Finally, numerical simulations and an image encryption application validate the effectiveness of the proposed approach. The results demonstrate that the method improves delay tolerance by allowing a larger sensor distribution ratio without modifying actuator placement, offering practical insights for the design of efficient and robust networked control systems.

This article focuses on the problem of adaptive practical fixed-time tracking control for a class of strict-feedback uncertain nonlinear systems subject to sensor faults. To achieve the control objective of this article, a series of radial basis function neural networks and a nonlinear fault-tolerant observer are introduced to approximate unknown nonlinearities and reconstruct unmeasurable states, respectively. Moreover, an adaptive fault compensation coefficient is employed to mitigate the effects of sensor faults, while the dynamic surface control technique is applied to alleviate the “differential explosion phenomenon” arising from the backstepping method. In addition, the proposed controller design method avoids the singularity problem inherent in fixed-time control strategies. Finally, the designed event-triggered controller can guarantee that all the signals are uniformly ultimately bounded in the presence of sensor faults, the tracking error converges to a small neighborhood of zero, the convergence time is independent of the initial system states and no Zeno behavior occurs.

This article is concerned with the issues of prescribed time bipartite synchronization (PTBS) for T-S fuzzy coopetition neural networks (CNNs) under a parameter optimization-based event-triggered control strategy and its application to image privacy protection. This study is motivated by three key considerations: first, the coexistence of competitive–cooperative interactions and T-S fuzzy rules makes the analysis of prescribed time synchronization more challenging; second, the goal of achieving PTBS while minimizing control costs necessitates the integration of control parameter optimization algorithms; and third, in industrial applications, ensuring the security of sensitive image data is of paramount importance. To address these challenges, an error system model is constructed by using the coordinate transformation method and IF–THEN fuzzy rules. Then, a fuzzy event-triggered switching controller without Zeno behavior is designed to trigger sampling for each fuzzy rule simultaneously. On this basis, a PTBS criterion for T-S fuzzy CNNs is established by using Lyapunov stability theory. To reduce control costs, a control parameter optimization algorithm based on the sparrow search algorithm is proposed for the first time. Finally, simulation results and applications in image privacy protection are provided, verifying the effectiveness and advantages of the control strategy in solving the PTBS problem.

This article studies the multisynchronization of delayed coupled neural networks (DCNNs) with general activation functions (AFs) via impulsive control. At first, a kind of AFs is proposed, and the $\boldsymbol {n}$ -neuron subnetwork with this kind of AFs can produce $\boldsymbol {(p+1)^{n}}$ locally stable equilibrium points (EPs) or periodic orbits (POs) by judging $\boldsymbol {2n(p+1)}$ algebraic inequalities and a nonsingular $\boldsymbol {M}$ -matrix. Compared with some specific AFs, such as the Sigmoid AFs or the saturated AFs, the AFs proposed in this article are more general. In addition, a kind of impulsive controller is designed. Compared with a continuous-time control strategy, the impulsive control strategy proposed in this article can reduce the communication cost and save bandwidth. Moreover, sufficient conditions are given to ensure both dynamical multisynchronization (DMS) and static multisynchronization (SMS) of DCNNs by building the comparison system and using the Lagrange method of variation of parameters. Lastly, an example is illustrated to testify to the validity of the obtained results.

This article addresses the issue of the event-triggered fixed-time consensus tracking control (ET-FT-CTC) for a class of strict-feedback nonlinear multiagent systems (NMASs) with unmeasurable states. The main challenges in these systems include partial unmeasurable states, completely unknown nonlinearities, and the occasional unavailability of the reference signal and its first-and second-order derivatives. To address these challenges, a nonlinear observer is designed to estimate the unmeasurable states, and a set of radial basis function neural networks (RBFNNs) are employed to approximate the unknown nonlinearities. Additionally, a novel update law is introduced to manage the unavailability of the reference signal. The dynamic surface control (DSC) approach is utilized to reduce the computational burden associated with the backstepping method, while a set of novel virtual controllers is constructed to avoid singularity problems. The proposed adaptive ET controller ensures that the CTC objective is achieved within a fixed time, without the occurrence of Zeno behavior. Two illustrative examples are provided to demonstrate the effectiveness of the proposed method.

This article investigates the security control problem of Markov jump systems (MJSs) under denial of service (DoS) attacks by constructing a class of discontinuous interval-dependent functional. Motivated by (1) the enhanced practicality and flexibility of multi-sensor sampled-data control with asynchronous packet arrivals and (2) the destabilizing impact of DoS-induced data loss, a resilient asynchronous sampled-data control (RASDC) scheme is designed. RASDC can send data once immediately after the attack, thereby alleviating the performance degradation caused by long-term no input. Furthermore, by utilizing the stability analysis idea of switched systems, a discontinuous interval-dependent functional is constructed, which combines the information of the resilient sampling interval and the attack interval. To overcome the analytical challenges posed by its discontinuities, the discrete-time Lyapunov stability theory, convex combination techniques, and some estimation methods are used to derive the sufficient condition for mean square asymptotic stability. In light of the stability criterion, a design algorithm for the secure controller is provided. Finally, simulation results demonstrate the effectiveness of the proposed approach.

This article is concerned with the secure control problem of memristive neural networks (MNNs) subject to deception attacks. To deal with the influence of deception attacks, a secure control scheme with a memory-dependent event-trigger (MDET) scheme is developed for MNNs while the desired performance can be guaranteed. Here, the MDET scheme is designed to remember the memory characteristic of dynamical process. On this basis, an interval-scheduled looped function (ISLF) is constructed. The feature of ISLF lies in that the positivity of Lyapunov functions can be dropped within the scheduled intervals and the rest are saved. Combined with discrete Lyapunov theory, inequality techniques, and continuous Lyapunov theory, some sufficient conditions are presented to ensure that the closed-loop MNNs are mean-square globally asymptotically stable in the presence of deception attacks. In contrast with the previous works, the improvements of the established trigger scheme and ISLF are well discussed. Lastly, simulation results are carried out to verify the effectiveness of the control scheme.

In this article, the exponential stabilization (ES) of delayed switched linear systems with asynchronous switching is settled via discrete dynamic event-triggered (DDET) control. First, an observer-based DDET scheme with a prescribed constant upper bound is devised. The DDET scheme can avoid the Zeno behavior directly and reduce the communication burden immensely. And the prescribed constant upper bound for the trigger interval can prevent the system performance from deteriorating. Under the framework of the DDET scheme, the situation of no system switching or multiple system switching over a trigger interval is considered, and a unified closed-looped system (CLS) which incorporates the above two situations is established. Then, by constructing a series of multiple Lyapunov functionals, the exponential stability of the unified CLS is studied based on the average dwell-time (ADT) method. Moreover, a design procedure for the feedback gain is provided. Finally, a simulation example is given to illustrate the effectiveness and superiority of the DDET scheme and the obtained main results.