Fixed-Time Consensus Tracking of Multiagent System Under DOS Attack With Event-Triggered Mechanism

Event-triggering mechanisms reported in the existing prescribed-time (PT) control do not adequately capture the dynamic nature of network environments, and are not applied to distributed consensus tracking problems with unknown time delays. Therefore, designing a dynamic event-triggering mechanism is crucial to ensuring PT stability, even in the presence of unknown time delays. This article focuses on developing a dynamic event-triggering mechanism to achieve adaptive practical PT output-feedback consensus tracking for nonlinear uncertain multiagent systems with unknown time delays. Firstly, a delay-independent PT state observer using a time-varying gain function is designed to estimate the immeasurable states. Following this, a novel distributed delay-independent PT consensus tracking scheme is constructed, incorporating a dynamic event-triggered mechanism through the command-filtered backstepping approach. In this design, dynamic variables based on a time-varying gain function are developed to support the event-triggering mechanism, ensuring practical stability within the prescribed settling time. Consequently, the proposed output-feedback control protocol can achieve practical PT stability, meaning that consensus tracking errors are constrained to a neighborhood around zero within a pre-specified time, regardless of the initial states of the agents or design parameters, while also avoiding the Zeno phenomenon. Finally, the effectiveness of the proposed strategy is validated through an illustrative example, which includes a comparative analysis.

In practice, disturbances, including model uncertainties and unknown external disturbances, are always widely present and have a significant impact on the cooperative control performance of a networked multi-agent system. In this work, the distributed consensus tracking control problem for a class of multi-agent systems subject to matched and mismatched uncertainties is addressed. In particular, the dynamics of the leader agent are modeled with uncertain terms, i.e., the leader’s higher-order information, such as velocity and acceleration, is unknown to all followers. To solve this problem, a robust consensus tracking control scheme that combines a neural network-based distributed observer, a barrier function-based disturbance observer, and a tracking controller based on the back-stepping method was developed in this study. Firstly, a neural network-based distributed observer is designed, which is able to achieve effective estimation of leader information by all followers. Secondly, a tracking controller was designed utilizing the back-stepping technique, and the boundedness of the closed-loop error system was proved using the Lyapunov-like theorem, which enables the followers to effectively track the leader’s trajectory. Meanwhile, a barrier function-based disturbance observer is proposed, which achieves the effective estimation of matched and mismatched uncertainties of followers. Finally, the effectiveness of the robust consensus tracking control method designed in this study was verified through numerical simulations.

Consensus tracking and vibration control for multiple single-link flexible manipulators with input signal quantization

This paper studies the fuzzy H ∞ control of nonlinear DC microgrids subject to the dynamic event-triggered mechanism (ETM), aperiodic DoS attacks, noises and mismatching premises. First, using the information of DC microgrid's T-S fuzzy model and aperiodic DoS attacks, a discrete-time resilient dynamic ETM is proposed, which can save constrained system resources, as well as actively exclude attack-induced dropouts and Zeno behaviour. Second, a fuzzy switched system model is built, which provides a unified platform to evaluate effects of all the affecting factors such as the dynamic ETM and DoS attacks. Third, by constructing a piecewise Lyapunov functional, criteria for exponential stability with guaranteed H ∞ performance are obtained, and an event-triggered fuzzy injection current controller is further designed. Simulation results confirm that, in the presence of aperiodic DoS attacks and noises, the proposed controller can stabilise the nonlinear DC microgrids, while the dynamic ETM works well in reducing the triggering rate without dropouts. Tradeoffs can be made between control and communication resources, and the proposed fuzzy controller achieves shorter settling times and smaller overshoots than the robust controller.

In this article, the asymptotic tracking consensus problem of higher-order multiagent systems (MASs) with general directed communication graphs is addressed via designing event-triggered control strategies. One common assumption utilized in most existing results on such tracking consensus problem that the inherent dynamics of the leader are the same as those of the followers is removed in this article. In particular, two cases that the dynamics of the leader are subjected, respectively, to bounded input and unknown nonlinearity are considered. To do this, distributed event-triggered observers are first constructed to estimate the state information of the leader. Then, local event-triggered tracking control protocols are designed for each follower to complete the goal of tracking consensus. One distinguishing feature of the present distributed observers lies in the fact that they could avoid the continuous monitoring for the states of the neighbors' observer states. It is also worth pointing out that the present tracking consensus control strategies are fully distributed as no global information related to the directed communication graph is involved in designing the strategies. Two simulation examples are finally presented to verify the efficiency of the theoretical results.

In this paper, a dual-channel event-triggered control (ETC) protocol with a state estimator is designed in multi-agent systems with switching topologies under denial-of-service attacks. Firstly, an ETC protocol and a dynamic ETC protocol are designed in the communication channel and the controller–actuator channel, respectively. Different from the traditional single-channel ETC, the dual-channel ETC is designed to further save resources. Second, an estimator is introduced to avoid continuous communication between agents. The sufficient conditions for realizing consensus are obtained under denial-of-service attacks. Moreover, due to the unstable communication topology of multi-agent systems, we designed a distributed controller based on switching topologies. Finally, the feasibility of the proposed method is verified through numerical simulations.

In this brief, we study the distributed consensus tracking control problem for multiple strict-feedback systems with unknown nonlinearities under a directed graph topology. It is assumed that the leader's output is time-varying and has been accessed by only a small fraction of followers in a group. The distributed dynamic surface design approach is proposed to design local consensus controllers in order to guarantee the consensus tracking between the followers and the leader. The function approximation technique using neural networks is employed to compensate unknown nonlinear terms induced from the controller design procedure. From the Lyapunov stability theorem, it is shown that the consensus errors are cooperatively semiglobally uniformly ultimately bounded and converge to an adjustable neighborhood of the origin.

This article addresses the finite-time consensus tracking control problem for nonlinear multiagent systems (MASs), in which state variables are unmeasured and nonlinear functions are totally unknown. An observer is designed to estimate state variables and fuzzy-logic systems are employed to approximate nonlinearities. Then, an observer-based adaptive fuzzy consensus tracking controller is developed by using the backstepping technique and constructing a novel barrier Lyapunov function with the consideration of the characteristics of MASs. The proposed control protocol can guarantee that: 1) all signals in the closed-loop system keep bounded and 2) the consensus tracking error converges to a prespecified region of the origin in the prescribed finite time. Compared with the existing observer-based finite/fixed-time control protocols, the settling time and the convergence region in our work can be both preassigned by the designer and not affected by the unknown positive constant, which lies in the Lyapunov derivative inequality. Finally, two comparison simulation examples, including a numerical example and a practical example, check the availability of the designed control scheme.

This paper investigates the secure synchronization control of Markovian jump neural networks (MJNNs) suffering from denial of service attacks (DoS attacks). The issue is presented for two reasons: 1) multiple sensors are generally used to measure the information of different state variables in practical networked control systems; 2) DoS attacks will disrupt the transmission of data packets in communication channels, thereby causing the system performance degradation. To deal with these problems, a multi-sensor-based switching event-triggered mechanism (SETM) is designed. More specifically, when the data packets are transmitted normally, the SETM will switch to an adaptive memory-based event-triggered mechanism, thereby saving the network resources. When the DoS attack occurs, the SETM will trigger immediately at the end of the DoS attack to improve the system performance. To facilitate the stability analysis, a merging time series is constructed by integrating the triggering instants of successful transmission and the ending instants of DoS attacks together. In light of the merging time series, a switched closed-loop system is established. Then, by utilizing the stability analysis idea of switched systems, a multiple Lyapunov functional is constructed, enabling the exploitation of multi-sampling. On this basis, a synchronization criterion is derived, accompanied by a co-design method for controller and the trigger matrices. Finally, the outcomes of the simulation confirm both the efficacy and the advantage of the suggested approach, especially when dealing with DoS attacks.

Event-based fixed-time synchronization of neural networks under DoS attack and its applications

Consensus tracking for higher-order multi-agent systems with switching directed topologies and occasionally missing control inputs

This article focuses on the problem of adaptive fuzzy consensus tracking control with event-triggered input for a class of fractional-order multiagent systems, where systems are considered to be with unmeasurable states, mismatched uncertain external disturbances, and unknown nonlinearities. An event-triggered mechanism with a decreasing threshold function is proposed in this article, which mitigates communication burden and avoids large control impulse. To achieve better tracking performance in distributed control strategy, a compensating fractional-order adaptation law associated with consensus tracking error is introduced when agents cannot obtain the information of reference trajectory directly. Under the fractional-order stability theory, a novel distributed adaptive event-triggered controller with fuzzy observers is constructed, which ensures the boundedness of tracking errors. A simulation example demonstrates the correctness of the presented scheme.

This article studies the problem of event-triggered adaptive fault-tolerant fuzzy output feedback consensus tracking control for nonlinear fractional-order multiagent systems with actuator failures under a directed graph. Considering the fact that the actual system works near the equilibrium point most of the time, a novel dynamic event-triggering strategy with the reset mechanism is proposed, where the dynamic threshold can be actively adjusted according to the preset conditions, so that the resource utilization can be further reduced. Based on an improved event-based consensus error, the state estimator about the derivative of reference trajectory and the adaptive law about the information of graph are constructed, which makes distributed consensus tracking control achieved without obtaining global information. Then, by introducing two adaptive compensating terms to deal with actuator failures and event-triggered measurement errors, it is shown in the sense of fractional-order stability criterion that tracking errors can converge to a compact set even if the fault parameters and modes are completely unknown. Finally, the correctness of the presented method is verified by a simulation example.

A distributed coordinated tracking problem is solved via a variable structure approach when there exists a dynamic virtual leader who is a neighbor of only a subset of a group of followers, all followers have only local interaction, and only partial measurements of the states of the virtual leader and the followers are available. In the context of coordinated tracking, we focus on both consensus tracking and swarm tracking algorithms. In the case of first-order kinematics, we propose a distributed consensus tracking algorithm without velocity measurements under both fixed and switching network topologies. In particular, we show that distributed consensus tracking can be achieved in finite time. The algorithm is then extended to achieve distributed swarm tracking without velocity measurements. In the case of second-order dynamics, we first propose two distributed consensus tracking algorithms without acceleration measurements when the velocity of the virtual leader is varying under, respectively, a fixed and switching network topology. In particular, we show that the proposed algorithms guarantee at least global exponential tracking. We then propose a distributed consensus tracking algorithm and a distributed swarm tracking algorithm when the velocity of the virtual leader is constant. When the velocity of the virtual leader is varying, distributed swarm tracking is solved by using a distributed estimator. For distributed consensus tracking, a mild connectivity requirement is proposed by adopting an adaptive connectivity maintenance mechanism in which the adjacency matrix is defined in a proper way. Similarly, a mild connectivity requirement is proposed for distributed swarm tracking by adopting a connectivity maintenance mechanism in which the potential function is defined in a proper way. Several simulation examples are presented as a proof of concept.

The leader-following consensus tracking control of fractional-order (FO) multi-motor systems (FOMMSs) in the presence of exogenous disturbances is investigated. It is widely recognized that FO models are better than integer-order (IO) ones for representing systems with memory effects. Therefore, studying the consensus tracking control of FOMMSs is essential. In this paper, a consensus tracking protocol is developed using a disturbance-observer and state feedback to deal with unknown exogenous disturbances. The closed-loop system stability is analyzed via Lyapunov and graph theory. Novel sufficient conditions for the stabilization of each motor are derived in the form of linear matrix inequalities. Simulation results illustrate the validity and efficacy of the proposed consensus protocol, namely its strong synchronization ability and robustness.