This study investigates the problem of achieving consensus within a prescribed time for general linear multiagent systems (MASs) operating over directed communication graphs, particularly when agents can only access relative output data via their onboard sensors. Under the assumption of strong observability, we design a periodic delayed output measurements-based distributed observer to recover the relative state information. Leveraging the reconstructed states, a linear time-varying control protocol is developed to ensure consensus is attained within the desired time. In contrast to conventional approaches, our method brings several key benefits. Most importantly, it removes the requirement for direct data exchange over the network, making the system inherently robust against cyber-attacks. Furthermore, the protocol is entirely distributed, which enhances adaptability to dynamic communication structures. At last, since the proposed method utilizes linear state feedback, it avoids the need for real-time solutions of system-related differential equations, thus reducing computational overhead. Numerical simulations demonstrate the efficacy of the proposed strategy.

This article aims to solve the exploratory coverage path planning (ECPP) and loop closure detection (LCD) problems of incremental simultaneous localization and mapping (iSLAM) for autonomous vehicles in an obstacle environment. An online ECPP method is proposed to enhance the overall performance of the planned trajectory while accommodating dynamic and incremental obstacle constraints. A novel probabilistic roadmaps trajectory homotopy (PRMTH) approach has been developed to navigate potential obstacles in environments with limited perception. An optimal multilayer map iSLAM method is proposed to update the map and improve the adaptability of obstacle avoidance for autonomous vehicles. Based on the ECPP method, ECPP and LCD mapping algorithms are developed considering the mapping coverage rate, trajectory length, and turning radius constraints. The final planning trajectory of the LCD is smoothed using the Dubins algorithm. A grid-based iSLAM method is proposed to address the challenges of map updating for autonomous vehicles operating in obstacle-rich environments. The results of the simulations and experiments show that the proposed ECPP and LCD strategies can provide an optimal solution to incremental simultaneous localization and mapping (SLAM) for autonomous vehicles.

This article proposes the dynamic event-triggered and self-triggered protocols to achieve the prescribed-time consensus of a class of nonlinear multi-agent systems with a trade-off performance. Firstly, a dynamic event-triggered control protocol and a time-varying parameter are jointly designed to accomplish the prescribed-time consensus. Secondly, a dynamic self-triggered control protocol is further designed to avoid continuous monitoring of the system states. The designed control protocols both can ensure the avoidance of the Zeno phenomenon and allow for dynamic adjustment between the specified time and the inter-event time. Specially, the minimum inter-event time can be designed as an arbitrarily large bounded constant when every agent is an integrator system. Finally, an example system is utilized to demonstrate the effectiveness of the designed algorithms.

This paper solves the problem of spacecraft rendezvous with input delay by designing the periodic event-triggered control (PETC) and periodic self-triggered control (PSTC), respectively. Firstly, a PETC based on the discrete-time parametric Lyapunov equation (DPLE) is designed to stabilize the delayed spacecraft rendezvous systems. Moreover, in order to avoid monitoring the measurement errors, a PSTC algorithm that the updates of the next control law depend on the previous triggered states is also designed. Specially, by using the properties of the DPLE, this new approach is not only simple, but also provides an easy and explicit condition on the only parameter of DPLE to guarantee the non-triviality of the designed PETC and PSTC. Finally, the effectiveness of theoretical results is verified by simulations. Note to Practitioners—Although this paper was inspired by the problem of spacecraft rendezvous, the designed algorithms can also be applied to other time-delay systems. Existing general event-triggered control methods have been used to solve the problem of spacecraft rendezvous for reducing the communication load, although this often complicates the design of the controller due to preventing the occurrence of Zeno phenomenon. To overcome this drawback, This paper proposes a periodic event-triggered control to achieve the spacecraft rendezvous with input delay, which naturally avoids the occurrence of Zeno phenomenon. In addition, a periodic self-triggered control is also designed, which has never been designed to solve the problem of delayed spacecraft rendezvous.

In recent years, the synchronization of coupled neural networks (CNNs) has been extensively studied. However, existing results heavily rely on assuming continuous couplings, overlooking the prevalence of intermittent couplings in reality. In this article, we address for the first time the synchronization challenge posed by intermittently CNNs (ICNNs) with coupling delay. To overcome the difficulties arising from intermittent couplings, we put forward a general piecewise delay differential inequality to characterize the dynamics during both coupled intervals and decoupled intervals. Based on the proposed inequality, we establish delay-independent synchronization criteria (DISCs) for ICNNs, enabling them to tackle general coupling delay. Notably, unlike previous studies, the achievement of synchronization in our approach does not rely on external control. Furthermore, for ICNNs that synchronize only under small delays, we formulate non-linear matrix inequality (LMI)-based delay-dependent synchronization criteria (DDSCs) that are computationally efficient and do not require delay differentiability. Finally, we provide illustrative examples to demonstrate our theoretical results.

Autonomous underwater vehicles (AUVs) face significant challenges in trajectory tracking due to nonlinear dynamics, actuator faults, and environmental disturbances. To address these issues, this article proposes a novel fault-tolerant control strategy that ensures fixed-time trajectory tracking with prescribed accuracy for underactuated AUVs. The proposed approach integrates boundary functions with a constraint-handling mechanism, enabling guaranteed tracking performance within a fixed time horizon while satisfying output constraints. Unlike existing approaches, the controller does not rely on accurate system models, parameter estimation, or external observers, and avoids the computation of virtual control derivatives, resulting in reduced computational complexity. Moreover, the control scheme maintains robustness against time-varying actuator faults and environmental disturbances without auxiliary adaptation or learning mechanisms. Simulation results demonstrate the effectiveness and superior performance of the proposed approach compared with existing methods, validating its capability to maintain tracking accuracy and closed-loop stability under adverse operating conditions.

The leader-following consensus problem for input constrained multiagent systems is investigated in this article. First, the follower agents are divided into several clusters based on the connectivity of the communication topology. Then, a novel clustered time-varying dynamic event-triggered mechanism (ETM) with adjustable minimum interevent time (MIET) is designed for each cluster, such that the follower agents within the same cluster share a unique ETM and are not influenced by agents in other clusters. Next, an event-triggered-based bounded control protocol with a time-varying gain and a parameter scheduler is proposed for each follower. Finally, the leader-following consensus can be realized with a faster convergence rate and the frequency of controller updates can be significantly reduced. Obviously, with the proposed clustered time-varying dynamic ETM, the Zeno-free phenomenon is guaranteed and the MIET can be modified by adjusting only a design parameter. Simulation results validate the effectiveness of the designed control algorithm.

This article establishes the linear static and dynamic time-varying event-triggered and self-triggered controllers with designable minimal interevent times (MIETs) to stabilize input constrained linear systems. We first design a static event-triggered control (ETC) algorithm, in which the control gain dependent on the solution to a parametric Lyapunov equation is time-varying and is only scheduled at a specified time decided by the static event-triggered mechanism (ETM). This can improve the control performance of the closed-loop system and save communication resources synchronously. Moreover, a dynamic ETC is designed to further increase the interevent times. Furthermore, in order to avoid the continuous monitoring of system status, the static and dynamic self-triggered control (STC) algorithms are also established. The Zeno phenomenon is avoided and the corresponding designable MIET is given in all established algorithms. Specifically, the designed control algorithms are extended to solve the corresponding semi-global stabilization problem. In some cases, the MIETs can be selected as an arbitrarily large bounded constant that has no relationship with system itself. Finally, applications to the spacecraft rendezvous control system verify the effectiveness of the designed algorithms.

This article designs the static and dynamic event-triggered control (ETC) and self-triggered control (STC) algorithms to achieve the semiglobal stabilization of discrete-time systems with input constraints. First, a novel static ETC algorithm based on the discrete-time parametric Lyapunov equation (DPLE) is designed. In order to further increase the interevent times (IETs), the corresponding dynamic ETC is designed. Next, both static and dynamic STC, where the next control law updates depend on the previous triggered states, are proposed to avoid monitoring the measurement errors. The proposed algorithms are not only capable of reducing the number of transmissions significantly but also build a very simple and clear relationship between the only design parameter and the nontrivial IET (NIET). This allows us to change regularly IETs by adjusting the design parameter so that the nontriviality of static and dynamic ETC and STC is guaranteed and a tradeoff between the IETs and the control performance can be easily found. Specifically, by exploring the properties of DPLE, the designed algorithms avoid the complex relationship between the nontrivial condition and the system matrices. Finally, the designed static and dynamic ETC and STC algorithms are applied to the design of the spacecraft rendezvous control system and their effectiveness is verified by simulation results.

This article proposes static/dynamic event-triggered and self-triggered discrete gain scheduled control with a designable parametric minimal interevent time (MIET) to achieve semiglobal stabilization of linear systems with input constraints. First, a novel static event-triggered discrete gain scheduled control, which can improve the control performance and simultaneously save the communication resources, is proposed by utilizing the properties of the parametric Lyapunov equation (PLE). Moreover, the static self-triggered mechanism, in which the next control law updates based on the previous triggered states, is also designed to avoid the monitoring of all states. In order to further increase the interevent times (IETs), the corresponding dynamic event-triggered and self-triggered discrete gain scheduled control are designed, respectively. All the proposed algorithms can not only avoid the Zeno phenomenon but also provide a designable parametric MIET. This allows to easily find a tradeoff between the IETs and the control performance by adjusting the only design parameter. In addition, by exploiting the properties of the PLE, the designed algorithms avoid the complicated relationship between the MIET and the system matrices. In some cases, the MIET can totally avoid the relationship with the system itself and be designed as an arbitrarily large bounded constant. Finally, applications to the spacecraft rendezvous system show the effectiveness of the established algorithms.