This article studies the event-triggered prescribed-time distributed observer network design problem of linear time-invariant systems subject to unknown input (UI), where each observer node has access only to partial output information of the target system. The issue of the prescribed-time distributed event-triggered state estimation has not been adequately addressed. To this end, a novel prescribed-time distributed unknown input observer (PTDUIO), featuring the periodic delayed terms and prescribed-time coupling gain, is proposed under the scenario of continuous-time communication. It is analytically proved that the constructed PTDUIO enables each observer node to reconstruct the target system's states in the prescribed settling time regardless of initial conditions, with completely eliminating the influence of UI. To reduce the communication frequency among neighboring nodes, an improved event-triggered mechanism with the triggering condition related to the prescribed-time function is designed. Such a design facilitates the simultaneous realization of prescribed-time convergence and event-triggered communication. In addition, the sufficient criterion is derived to achieve the practical prescribed-time distributed state estimation in the event-triggered communication fashion, and the Zeno behavior is excluded. Finally, numerical examples are provided to demonstrate the effectiveness and superiority of the designed PTDUIO.

This article is dedicated to solving the cooperative collision-free target fencing control problem for a class of multiple unmanned surface vehicle (multi-USV) systems subject to external disturbances and uncertain dynamics. While existing control strategies often struggle to simultaneously address external disturbances, internal system uncertainties, and safety constraints in real-world applications, this study proposes a robust two-stage control strategy to effectively tackle these challenges. In the first stage, a baseline controller leveraging sliding mode control (SMC) is developed to effectively compensate for external disturbances and establish fundamental target fencing capabilities. Building on this foundation, the second stage introduces an advanced controller enhanced by soft actor–critic (SAC) reinforcement learning (RL) technique, which is specifically tailored to address internal system uncertainties and guarantee collision avoidance. Finally, numerical simulations are performed to validate the proposed approach, demonstrating its advantages over conventional RL-based methods in terms of efficiency.

This article addresses the resilient consensus problem of multiagent systems subject to cyber attacks on communication links, where the attacks on different links may collude to maintain undetectable. For the case with noncollusive attacks on links, a distributed fixed-time observer is designed so that the attack on each link can be detected by the two associated agents. A necessary and sufficient condition is derived to ensure the isolation of attacked links and no mistaken isolation of normal ones. For the case with collusive attacks on links, a novel attack isolation algorithm is proposed by constructing extra observers on the basis of the previous designed distributed fixed-time observer via sequentially removing the information associated with one of the links. Based on the isolation of the attacked links, a control algorithm is designed, and a necessary and sufficient condition is provided to achieve resilient consensus. Numerical examples corroborate the effectiveness of the proposed strategies.

This article focuses on solving the synchronization problem of neural networks (NNs) in the presence of denial-of-service (DoS) attacks and communication delays. Specifically, an attack detection algorithm constructed based upon the acknowledgment (ACK) signal is provided to detect the sleeping and active intervals of DoS attacks. To reduce information transmission during the synchronization-seeking process, a new kind of Lyapunov function-based resilient event-triggered mechanism (ETM) is designed to modulate the information transmission between the master and slave systems. Then, an event-based impulsive controller is designed to achieve synchronization in the master–slave systems with event-triggered communication and communication delay between the event generator and the controller, where the impulsive control instants are produced by the resilient ETM rather than prescribed. Furthermore, a resilient sampled-data-based ETM and an event-based controller consisting of hybrid state feedback and impulsive controllers are developed. Under the proposed ETMs and controllers, some sufficient yet efficient criteria are derived to guarantee the master–slave synchronization of NNs. The influence of the attack parameters and triggering parameters on the synchronization performance is also discussed. Finally, two numerical examples and an application in image encryption and decryption based on the master–slave chaotic systems are given to demonstrate the effectiveness of the theoretical results.

This article addresses the dynamic task allocation problem with limited communication and velocity. The main challenge lie in the selection of$k$fittest winner participants and the participant contention that one winner participant may be selected by multiple targets simultaneously. Existing methods take the distance between the targets and participants as the evaluation index to select winners, which may lead to futile selection since the winner participant locating at the opposite direction of the target cannot intercept the target with limited velocity. By carefully considering both the distance between the targets and participants and the motion direction of the targets, an improved evaluation index for each target is proposed and employed such that the futile selection can be avoided in the executing process of the algorithm. Moreover, an extra evaluation index for each winner participant is presented to select one winner target to overcome the participant contention. Based on these, the control protocols are developed for targets interception, and their stability is proven by the Lyapunov theory under some suitable conditions. Finally, simulation examples are presented to illustrate the effectiveness and advantages of the proposed algorithms.