An enhanced control scheme for multiagent cooperative output regulation (COR) is presented in this paper. The proposed scheme incorporates prescribed-time observers and controllers with concurrent learning adaptive laws. By introducing prescribed-time event-triggered (ET) observers, the estimation of exosystem information can be achieved within a prescribed time, eliminating continuous communication between followers and avoiding reliance on global information. Additionally, Zeno behavior is excluded. The convergence of controller parameters is ensured by the established concurrent learning adaptive laws. Specifically, the challenge of designing correlation filter signals caused by the lack of a matching condition between the exosystem matrix and the follower system matrix, essential for concurrent learning, is addressed by employing the regulator equation. The desired relationship between two sets of developed filtered signals is ensured by the developed prescribed-time observers after a prescribed time. This establishes the basis for a concurrent learning strategy. Moreover, a cooperative controller with cooperative adaptive laws is developed, effectively addressing the difficulty arising from the mismatch between the matrix estimation of the exosystem and the regulator equation. Compared with existing studies, the developed controller can accurately identify controller parameters, resulting in better system performance. The successful application of the cooperative finite-time excitation (CFTE) condition relaxes the widely used persistent excitation (PE) and cooperative persistent excitation (CPE) conditions in parameter identification. Finally, a multi-robot formation simulation verifies the effectiveness of the developed method. Note to Practitioners—The COR problem explored in this paper can be applied to address the actual robot formation issue, utilizing coordinate transformation. Unlike existing studies, this paper employs easily satisfied cooperative persistent excitation conditions, making them readily applicable to real-world systems. The developed approach enables the convergence of the designed controller parameters to their true values, achieving superior control effects. Moreover, this paper overcomes some current research difficulties. It successfully integrates the most advanced event-triggered mechanism (ETM) into the prescribed-time observer, realizing the prescribed-time observation of the exosystem. Uniquely, the method presented here does not depend on global information, making it suitable for complex large-scale multiagent connections and the Internet of Things. It holds significant guidance for practical multiagent networked systems. The effectiveness of the proposed method is demonstrated through a nonholonomic dynamic robot formation problem. It is anticipated to be scalable to multiagent systems (MASs) with broader practical constraints, finding applications in more realistic engineering scenarios.

This paper addresses the distributed consensus issue of linear multiagent systems (MASs) subject to disturbances. First, a fully distributed adaptive control law is established for each agent, removing the assumption that global information should be known prior. Additionally, unlike existing consensus studies, the restrictions on continual communication among agents and constant controller updates are eliminated through the designed state observers and event-triggered conditions (ETCs). Moreover, an innovative event-triggered condition (ETC) is created that, via the inclusion of a dynamic parameter, captures mixed triggering and time-varying thresholds as special cases. Particularly, distinct from some dwell time methods that enforce inter-event time (IET) greater than zero at the expense of asymptotic stability, positive inter-event times (IETs) and asymptotic stability can be guaranteed simultaneously by the suggested event-triggered conditions (ETCs) in the absence of disturbances. Furthermore, positive minimum inter-event times (MIETs) can be maintained even in the presence of disturbances, which indicates the robustness of the proposed event-triggered mechanism (ETM). It is shown that the suggested technique performs disturbances suppression for all agents in a completely distributed manner while omitting Zeno behavior. Finally, a simulation example demonstrates the suggested scheme’s efficacy. Note to Practitioners—The multiagent consensus problem is considered in this paper, which can be applied to some practical systems, e.g., the unmanned aerial vehicles formation problems, as the control objective in these applications can be converted into the consensus problem of MASs. Different from existing results, a novel ETM is proposed, reducing agents’ communication and preventing continuous controller updates. In addition, disturbances widely exist in engineering. The proposed method ensures that the interval between two consecutive event triggers is greater than a small positive constant. Therefore, it is helpful for applying the proposed method in practical engineering. Finally, the established method is applied to a two-mass-spring control problem, and the effectiveness is illustrated. It is anticipated that the proposed approach can be extended to MASs with more realistic network-induced constraints and applied to more practical engineering systems.

This paper presents a fully distributed, reliable output regulation scheme on the basis of a dynamic memory event-triggered mechanism for a class of linear heterogeneous multiagent systems under actuator faults. First, dynamic memory event-triggered mechanisms are established by introducing historical information on dynamic variables. Rigorous analysis shows that the developed dynamic memory event-triggered mechanisms produce larger event intervals than the existing memoryless dynamic event-triggered mechanism. Furthermore, in cases where only a portion of the followers possess knowledge about the exosystem matrix, an open-loop estimation approach is devised to circumvent the need for ongoing communication among the followers. In contrast to the current approach for intermittent communication through open-loop estimation, the proposed approach removes the need for all agents to possess identical and pre-known system matrices. Additionally, the proposed scheme enables all followers to obtain cooperative fault-tolerant output regulation fully distributed while avoiding Zeno behavior. Finally, the efficacy of the developed strategy is substantiated by simulation results.Note to Practitioners—This study focuses on the issue of multiagent cooperative output regulation, which has practical applications in various systems, including robot formation and satellite formation. In such scenarios, the control objective can be transformed into the issue of achieving cooperative output regulation in multiagent systems. Unlike the existing works, this study introduces a novel dynamic memory event-triggered mechanism aimed at enhancing the minimum event-triggered intervals. In addition, actuator faults are prevalent in engineering. The developed scheme ensures the reliable operation of the controlled system, with minimum event-triggered intervals larger than small positive constants. Constant communication between agents is avoided, which is beneficial for application in practical systems. Ultimately, the effectiveness of the scheme is verified through applications in mobile robot formation and satellite formation. The proposed method is anticipated to be expandable to multiagent systems characterized by a wider range of practical limitations and to be utilized in more realistic practical engineering.

In this article, we address the$H_{\infty }$control problem for a class of Takagi-Sugeno (T-S) fuzzy systems, where the premise variables often work in some fuzzy sets. By combining the properties of the product inference engine and set theory, we develop a membership function-dependent$H_{\infty }$index, enhancing disturbance suppression by assigning diverse weights to various subsystem$H_{\infty }$indices. An advanced event-triggered mechanism, utilizing dynamic memory variables, is proposed to expand the threshold and conserve resources, outperforming conventional dynamic event-triggered mechanisms (DETM). Theoretical analysis indicates that the dynamic memory event-triggered mechanism (DMETM) offers a more extensive event-triggered interval than the conventional memoryless DETM. Furthermore, in the proposed DMETM, a system-related dynamic variable is designed to replace the corresponding constant coefficient, increasing design flexibility and relaxing the design constraints of current state-of-the-art DETMs. Specifically, by constructing a monotonic nonincreasing bounded function, the system information is successfully integrated into the design of the dynamic coefficient. This design allows the threshold of the event-triggered condition to be adjusted more flexibly according to the system's operational status, thereby improving the practicality of the scheme in real-world applications. Besides, Zeno behavior is avoided. Finally, the effectiveness of the scheme is verified by an example.

In this article, the problem of event-triggered fixed-time tracking control for nonlinear systems with state constraints and dead zone is considered. First, for state-constrained problems, the state transformation technique is applied to remove the restriction that the virtual control input needs to satisfy the “feasibility condition.” Second, to deal with dead zone, fixed-time compensation filters are introduced. Different from the existing compensating filters, the proposed filter can make the filter state converge faster to better eliminate the effect of dead zone by introducing higher-order terms of the filter state. To avoid the “explosion of complexity” problem inherent in backstepping, fast fixed-time filters (FFTFs) are developed. Unlike the existing first-order filters and fixed-time filters (FTFs), the proposed filters can achieve faster convergence of the filtering state. Unlike the existing dynamic event-triggered mechanism (DETM), the proposed improved DETM has larger event-triggered intervals (ETIs) and is more resource-saving, by adding two dynamic variables adjusted by historical triggered information. Furthermore, the proposed control scheme guarantees that: all states are within constraints, all closed-loop system signals are bounded, and tracking error converges to an arbitrarily small neighborhood of the origin in a fixed time. Finally, a jerk circuit system verifies the efficacy of the proposed method.

This article considers the problem of cooperative fault-tolerant output regulation of linear heterogeneous multiagent systems with actuator faults where the exosystem matrix is known by part of the followers. An adaptive dynamic event-triggered scheme is proposed to avoid continuous communication between followers, removing the assumption that global information should be known for controller design. Different from the existing open-loop estimation method for obtaining intermittent communication, the approach proposed in this article does not require that the system matrices of all agents be the same and known a prior. Compared with the existing static or periodic event-triggered mechanism (ETM), by introducing dynamic variables, a more general form than an exponential function, the proposed adaptive dynamic event-triggered condition provides the potential to save energy and obtain better performance. It is demonstrated that the suggested event-triggered control (ETC) method performs cooperative fault-tolerant output regulation for all followers in a completely distributed way with intermittent communication while excluding Zeno behavior. Finally, a simulation example is carried out to illustrate the efficacy of the suggested strategy.

This article considers the$H_{\infty }$control problem in the finite-time horizon for a class of Takagi–Sugeno (T–S) fuzzy systems that frequently work under a certain fuzzy rule. By assigning different weights to$H_{\infty }$indexes of different subsystems, a novel finite-time membership-function-dependent$H_{\infty }$performance is proposed. Then, better disturbance rejection can be achieved for this specific type of T–S fuzzy system. In order to save the system resources, an event-triggered mechanism is developed. Different from the widely existing dynamic event-triggered mechanism, a dynamic memory event-triggered mechanism is established by introducing dynamic variables with memory. Rigorous theoretical analysis shows that the proposed dynamic memory event-triggered mechanism possesses larger event-triggered intervals than the existing dynamic event-triggered mechanism. This facilitates the implementation of the proposed scheme in real systems, as real physical components require time intervals between successive event executions. Furthermore, based on the newly proposed index and dynamic memory event-triggered mechanism, the finite-time event-triggered$H_{\infty }$control problem of the considered system is solved. Finally, a practical example is employed to display the efficacy of the proposed scheme.

In this article, a new cooperative control protocol with parameter convergence is developed to address the problem of cooperative output regulation (COR) of linear multiagent systems (MASs). First, the utilization of the regulator equation overcomes the difficulty of related filtering signal design owing to the absence of matching conditions between the leader system matrix and that of the followers, which is essential for concurrent learning. Then, with the light of the proposed observer, a specific relationship between two sets of constructed filtered signals is satisfied after a finite time, which lays the foundation for a concurrent learning strategy. Furthermore, a cooperative controller with the cooperative adaptive law is successfully constructed, which overcomes the difficulty of controller design caused by estimations of the leader system matrix not satisfying regulator equation. Compared with the existing studies, the cooperative finite-time excitation (cFTE) condition is successfully applied to the COR of MASs for the first time. The developed controller can ensure accurate identification of adaptive parameters and output regulation control simultaneously. As a result, better system performance can be achieved. Finally, the effectiveness of our method is verified by a simulation example.

The distributed fault-tolerant (FT) consensus control problem of linear multiagents with disturbances is considered in this article. For undirected graphs, first, by introducing adaptive control coefficients, multiagent reliable control can be carried out fully distributed, removing the assumption that global information should be known prior. Furthermore, different from existing consensus FT studies, the limitation of continuous communication among agents is removed by developing an open-loop estimation and event-triggering mechanism (ETM). Particularly, distinct from some dwell-time methods that enforce an interevent time greater than zero at the expense of asymptotic stability, by introducing timer variables, positive interevent time and asymptotic stability can be guaranteed simultaneously by the proposed ETM in the absence of disturbances. Furthermore, a minimum positive trigger interval can be maintained for each agent even in the presence of disturbances, indicating the robustness of the event-triggered strategy. It is demonstrated that the suggested event-triggered control method performs reliable disturbance suppression for all agents in a completely distributed way with intermittent communication while excluding the Zeno behavior. Moreover, we try to generalize our results to directed strong connectivity. Finally, simulation examples are carried out to illustrate the efficacy of the suggested scheme.

This article focuses on disturbance attenuation problem for discrete-time Takagi-Sugeno (T-S) fuzzy systems. First, a membership function-dependent H∞performance index is proposed, by which, different performance can be achieved for local subsystems. Then, the better performance may be obtained for the T-S fuzzy system that works on a particular local subsystem most of the time. It may guarantee better control effects in practical engineering applications. With the help of the newly defined performance index and fuzzy Lyapunov functions, an observer-based feedback control scheme is presented in the form of linear matrix inequalities. In simulation, the performance index obtained by this article can be improved by about 10% than that obtained by the traditional H∞control method.