This article investigates the event-triggered (ET) consensus issue of Lipschitz nonlinear multiagent systems (MASs) with a positive minimum inter-event time (MIET) in the presence of unmeasurable state. To handle this issue, we design a fully distributed control scheme by virtue of asynchronous event-triggered mechanism (ETM) and available local measurement output, in which the knowledge of global information is no longer required by introducing adaptive parameters. It is shown that under the proposed control scheme, the consensus is asymptotically realized, in which the local state observer is proposed to remove the requirement of full-state information. Besides, a dynamic variable is introduced to obtain a positive MIET in the proposed ETM, where each agent asynchronously sends its observer value to its neighbors based on intermittent communication. In light of consensus analysis and MASs dynamics, a novel estimator of the observer is designed to ensure the asymptotic consensus. Note that based on the reformulated Lipschitz property, the linear matrix inequality (LMI) conditions of the control design are less restrictive as compared with the exist results. A practice simulation example is presented to verify the theoretical results.Note to Practitioners—Some practical (such as manipulator and pendulum) control systems can be modeled as Lipschitz nonlinear MASs. If the information exchange determined by ETM is high-frequency, it is unsuitable for physical implementation because each agent has limited communication resource. Thus, it is significant to design ETM with a positive MIET guarantees. Besides, the asynchronous communication among neighbors is more distributed compared with the synchronous communication, which might significantly save the communication resource. The reformulated Lipschitz property is introduced to reduce conservatism of the LMI conditions in the existing results. It might be difficult to measure the full-state information of each agent in some situations owing to physical limitations. Therefore, an observer-based adaptive asynchronous ET control scheme is proposed for Lipschitz nonlinear MASs with unmeasurable state, which can guarantee asymptotic convergence and a positive MIET. Finally, a one-link manipulator with revolute joints is considered to demonstrate the effectiveness of the proposed algorithm.

This article considers the observer-based containment control problem of multiagent systems (MASs), with a focus on the scenario where the control task only utilizes intermittent communication among agents and from the sensor to the local state observer. To deal with this problem, we propose a hybrid triggering control strategy, which includes two parts. First, a local observer for each follower is proposed to estimate state under a time-triggered mechanism (TTM). Second, based on local observer, a fully distributed containment controller is proposed under a node-based hybrid triggering mechanism (HTM), which does not require global information. Note that such HTM includes a TTM and a dynamic event-triggered mechanism (DETM). The most significant merit of this article is that the TTM is developed to provide the guarantee of the positive minimum triggering interval time (MTIT) between two triggering actions, which is more desirable than simply excluding Zeno behavior in practical applications. Finally, a simulation example on containment of nonholonomic mobile robots illustrates the control strategy.

This article addresses the output consensus problem of heterogeneous multiagent systems (MASs) via a distributed modified dynamic event-triggered control design. First, a fully distributed asynchronous event-triggered compensator for each agent is proposed to act as a virtual reference generator without using global information. Second, based on this compensator, a distributed event-triggered controller for each heterogeneous agent is developed to reach output consensus. Specifically, to save resources and guarantee asymptotic consensus, a modified dynamic event-triggered mechanism (DETM) is proposed, in which a time-triggered mechanism (TTM) is introduced to ensure the existence of a positive minimum interevent time and a DETM is designed to further avoid redundant triggering actions. Besides, the triggering condition of the DETM does not require continuous detection, it is only detected when the timer variable in the TTM deceases from maximum value to zero. These features of the developed control scheme are presented analytically and verified numerically.

This article investigates the leader–follower consensus tracking problem for Lipschitz nonlinear multiagent systems (MASs) with unmeasurable states. To address limitations in communication and sensing resources, a hybrid triggering consensus framework is proposed to reduce redundant transmissions and measurements. First, a local observer is designed to estimate the system state, where output sampling and transmission to the observer are determined by a time-triggered mechanism (TTM). Then, based on the observer and two nonlinear estimators, a fully distributed controller is developed. Communication among neighboring agents is governed by a hybrid triggering mechanism (HTM) that integrates both time-triggered and event-triggered conditions. Notably, the proposed strategy ensures a positive minimum triggering interval (PMTI). The effectiveness of the proposed method is validated on a single-link flexible joint manipulator.

This article is focused on the output synchronization or tracking problem for heterogeneous uncertain nonlinear multiagent systems (MASs) affected by denial-of-service (DoS) attacks, which realizes the two joint objectives, namely output synchronization and parameter estimation. Different from the recent works, where neighbors of the leader can access the state of the leader, only part output information of the leader is available for its neighbors in this article. In addition, the system matrix of the leader only is known to neighbors of the leader. In order to estimate the state and system matrix of the leader and resist the effect of DoS attacks, a distributed resilient observer is proposed by employing a jointly observable condition. Moreover, to derive precise adaptive learning of unknown parameters in uncertainties, a data-driven learning method is introduced. Consequently, a novel resilient output synchronization control framework is proposed, in which the interesting fact is that exponential convergence of both output synchronization errors and parameter estimation errors to zero can be arrived simultaneously. Finally, a simulation example is presented to reveal the effectiveness of the developed control scheme.Note to Practitioners—The multiagent output synchronization problem is studied in this paper, which can be applied to some many practical control systems with uncertain parameters. In many practical applications, owing to physical or geographical limitations, it is usually not easy for neighbors of the leader to directly measure the full state or output of the leader. A single agent might be able to obtain only partial output of the leader. In addition, the actual networked MASs are vulnerable to cyber attacks caused by malicious attackers, which can lead to output synchronization degradation or instability. Therefore, in this paper, an adaptive resilient synchronization control scheme is developed for MASs with parameter uncertainties under jointly observable condition. In simulations, a two-mass-spring system is used to illustrate the effectiveness of the proposed control scheme.

The output consensus or tracking problem for heterogeneous multiagent systems (MASs) under jointly observable condition (JOC) is investigated in the presence of unknown system matrix of the leader and unknown faults on communication link and actuator. Unlike the recent works, where neighbors of the leader have access to the state information of the leader, only part output information of the leader can be measured by its neighbors under JOC in this article. In addition, the system matrix of the leader only is known to neighbors of the leader. The problem of unknown leader’s state and unknown leader’s system matrix, unknown communication link faults (CLFs) is transformed into constructing the fully distributed state and system matrix observers by virtue of adaptive control technique and JOC. In light of the developed distributed observer, a distributed adaptive fault-tolerant controller against actuator faults is designed. Here, compared with the existing ideas, actuator faults of an agent will not affect the dynamics of its neighbors over the communication graph in this article. It is shown that the output of each follower asymptotically converges to the output of the leader. Finally, the developed control scheme is illustrated by a simulation example.

This article studies the asymptotic tracking control problem for strict-feedback nonlinear systems affected by asymmetric state and input constraints, nonparametric uncertainties, actuator faults, and unknown virtual control coefficients (VCCs). Different from the previous tracking control for strict-feedback systems results, the class of systems considered is more general, while can achieve better tracking performance in term of asymptotic tracking. A nonlinear state-dependent function (NSDF) is introduced to handle full-state constraints without requiring feasibility conditions imposed on virtual controls. To deal with the “explosion of complexity”, a novel filter is developed, which can also guarantee that the boundary errors asymptotically converge to zero. To cope with unknown VCCs, a Lyapunov function is developed based on the lower bounds of unknown VCCs skillfully. By introducing the Nussbaum function and a novel smooth function, the obstacle jointly caused by input constraint and actuator faults is circumvented well. It is proved that the asymptotic convergence of tracking error is successfully ensured. Finally, simulation verification is provided to illustrate the effectiveness of theoretical results.