Showing papers on "Consensus published in 2022"

Human-in-the-Loop Consensus Control for Nonlinear Multi-Agent Systems With Actuator Faults

Abstract: This paper considers the human-in-the-Ioop leader-following consensus control problem of multi-agent systems (MASs) with unknown matched nonlinear functions and actuator faults. It is assumed that a human operator controls the MASs via sending the command signal to a non-autonomous leader which generates the desired trajectory. Moreover, the leader's input is nonzero and not available to all followers. By using neural networks and fault estimators to approximate unknown nonlinear dynamics and identify the actuator faults, respectively, the neighborhood observer-based neural fault-tolerant controller with dynamic coupling gains is designed. It is proved that the state of each follower can synchronize with the leader's state under a directed graph and all signals in the closed-loop system are guaranteed to be cooperatively uniformly ultimately bounded. Finally, simulation results are presented for verifying the effectiveness of the proposed control method.

Human-in-the-Loop Consensus Control for Nonlinear Multi-Agent Systems With Actuator Faults

Abstract: This paper considers the human-in-the-Ioop leader-following consensus control problem of multi-agent systems (MASs) with unknown matched nonlinear functions and actuator faults. It is assumed that a human operator controls the MASs via sending the command signal to a non-autonomous leader which generates the desired trajectory. Moreover, the leader's input is nonzero and not available to all followers. By using neural networks and fault estimators to approximate unknown nonlinear dynamics and identify the actuator faults, respectively, the neighborhood observer-based neural fault-tolerant controller with dynamic coupling gains is designed. It is proved that the state of each follower can synchronize with the leader's state under a directed graph and all signals in the closed-loop system are guaranteed to be cooperatively uniformly ultimately bounded. Finally, simulation results are presented for verifying the effectiveness of the proposed control method.

Fully Distributed Scaled Consensus Tracking of High-Order Multiagent Systems With Time Delays and Disturbances

Abstract: This article focuses on scaled consensus tracking for a class of high-order nonlinear multiagent systems Different from the existing results, for high-order nonlinear multiagent systems with time delays and external disturbances, a fully distributed consensus protocol is designed to drive all agents to achieve scaled consensus with preassigned ratios The control gains are varying and updated by distributed adaptive laws As a result, the presented protocol is independent of any global information, and thus, could be implemented in a fully distributed manner Simultaneously, the fully distributed control protocol using an adaptive $\sigma$ -modification technique is presented to deal with external disturbances, which can guarantee the tracking errors and coupling weights of all following agents are uniformly ultimately bounded To tackle with the derivatives of the functionals with time delays, the Lyapunov–Krasovskii functional is employed to analyze and compensate them by introducing multiintegral terms Finally, simulation examples are included to verify the effectiveness of the theoretical results

Fully Distributed Scaled Consensus Tracking of High-Order Multiagent Systems With Time Delays and Disturbances

Abstract: This article focuses on scaled consensus tracking for a class of high-order nonlinear multiagent systems. Different from the existing results, for high-order nonlinear multiagent systems with time delays and external disturbances, a fully distributed consensus protocol is designed to drive all agents to achieve scaled consensus with preassigned ratios. The control gains are varying and updated by distributed adaptive laws. As a result, the presented protocol is independent of any global information, and thus, could be implemented in a fully distributed manner. Simultaneously, the fully distributed control protocol using an adaptive $\sigma$ -modification technique is presented to deal with external disturbances, which can guarantee the tracking errors and coupling weights of all following agents are uniformly ultimately bounded. To tackle with the derivatives of the functionals with time delays, the Lyapunov–Krasovskii functional is employed to analyze and compensate them by introducing multiintegral terms. Finally, simulation examples are included to verify the effectiveness of the theoretical results.

Fixed-Time Event-Triggered Output Consensus Tracking of High-Order Multiagent Systems Under Directed Interaction Graphs

Abstract: This article investigates the problem of fixed-time event-triggered output consensus tracking for high-order multiagent systems (MASs) under directed interaction graphs. First, a fixed-time event-triggered distributed observer and triggering functions are proposed. Next, fixed-time convergence of the presented distributed observer is proved by the Lyapunov function approach, and an analysis is conducted to show the proposed distributed observer excludes zeno behavior. Then, an event-triggered adaptive dynamic surface fixed-time controller is designed to stabilize the tracking error system. Finally, simulation results are given to show the effectiveness and superiority of the consensus scheme developed. The contribution of this article is to present a novel event-triggered fixed-time distributed observer and a novel fixed-time controller, which can reduce frequency of communication and control update, avoid continuous monitor, exclude zeno behavior, eliminate the effect of mismatched disturbance caused by observation error, and achieve practical fixed-time output consensus tracking of high-order MAS under directed interaction graphs.

Learning-Based Distributed Resilient Fault-Tolerant Control Method for Heterogeneous MASs Under Unknown Leader Dynamic

Abstract: In this article, we consider the distributed fault-tolerant resilient consensus problem for heterogeneous multiagent systems (MASs) under both physical failures and network denial-of-service (DoS) attacks. Different from the existing consensus results, the dynamic model of the leader is unknown for all followers in this article. To learn this unknown dynamic model under the influence of DoS attacks, a distributed resilient learning algorithm is proposed by using the idea of data-driven. Based on the learned dynamic model of the leader, a distributed resilient estimator is designed for each agent to estimate the states of the leader. Then, a new adaptive fault-tolerant resilient controller is designed to resist the effect of physical failures and network DoS attacks. Moreover, it is shown that the consensus can be achieved with the proposed learning-based fault-tolerant resilient control method. Finally, a simulation example is provided to show the effectiveness of the proposed method.

Adaptive NN-Based Consensus for a Class of Nonlinear Multiagent Systems With Actuator Faults and Faulty Networks

Abstract: This article addresses the problem of fault-tolerant consensus control of a general nonlinear multiagent system subject to actuator faults and disturbed and faulty networks. By using neural network (NN) and adaptive control techniques, estimations of unknown state-dependent boundaries of nonlinear dynamics and actuator faults, which can reflect the worst impacts on the system, are first developed. A novel NN-based adaptive observer is designed for the observation of faulty transformation signals in networks. On the basis of the NN-based observer and adaptive control strategies, fault-tolerant consensus control schemes are designed to guarantee the bounded consensus of the closed-loop multiagent system with disturbed and faulty networks and actuator faults. The validity of the proposed adaptively distributed consensus control schemes is demonstrated by a multiagent system composed of five nonlinear forced pendulums.

Event-Triggered Guaranteed Cost Leader-Following Consensus Control of Second-Order Nonlinear Multiagent Systems

Abstract: This article deals with the event-triggered leader-following guaranteed cost consensus control problem for second-order nonlinear multiagent systems, in which the guaranteed cost function is proposed to facilitate to enhance the consensus tracking regulation performance. To reduce the frequency of information transmission, a distributed event-triggered mechanism, which broadcasts the triggered states to its neighbours for each agent, is designed, and the triggering condition is then constructed for leader-following second-order nonlinear multiagent systems. By employing Lyapunov–Krasovskii method and Barbalat’s lemma, some sufficient conditions are derived to ensure the leader-following consensus and guaranteed cost performance for second-order nonlinear multiagent systems. It is also exhibited that the constructed triggering condition can efficaciously exclude the Zeno behavior. To testify the efficacy of the proposed theoretical methodology, a simulation example is offered.

Leader-Following Consensus for a Class of Nonlinear Multiagent Systems Under Event-Triggered and Edge-Event Triggered Mechanisms

Abstract: Considering that there are many systems with limited network bandwidth in practice, this article studies the leader-following consensus problem for a class of nonlinear multiagent systems (MASs). The purpose of this article is to reduce unnecessary information transmission between any pair of adjacent agents including the leader in the MASs through intermittent communication. The novel event-triggered and asynchronous edge-event triggered mechanisms are designed for the leader and all edges, respectively. The static and dynamic consensus protocols under these mechanisms are proposed to address the leader-following consensus problem for MASs with Lipschitz dynamics, and the systems will not exhibit Zeno behavior under these two control schemes. Note that the dynamic consensus protocol does not rely on any global values of MASs, it is a fully distributed way. Finally, a practice simulation example is introduced to illustrate the theoretical results obtained.

Adaptive bipartite consensus of competitive linear multi‐agent systems with asynchronous intermittent communication

Abstract: In this article, bipartite consensus is investigated for linear multi‐agent systems (MASs) via adaptive asynchronous intermittent control. Adaptive asynchronous intermittent bipartite consensus protocols are proposed for MASs with antagonistic links under both fixed and connected switching topologies. By using gauge transformation and stability theory, convergency analysis is given and some conditions of bipartite consensus are obtained. It is turned out that bipartite consensus can be realized if the communication rate is no less than a threshold under the assumption that the network is connected and structurally balanced. Finally, two simulation examples are provided to verify the effectiveness of the obtained results.

Consensus Switching of Second-Order Multiagent Systems With Time Delay

Abstract: This technical correspondence studies the consensus problem for second-order multiagent systems under network topologies with a directed spanning tree. Consensus analysis for systems with the distributed delayed proportional-integral (PI)-type controller is given. Crossing directions of the characteristic roots can be identified by a sufficient condition. If the rightward crossing condition holds, the delay margin can be obtained to guarantee that the systems reach consensus if and only if the time delay is less than the critical value. Otherwise, it is possible that the systems switch from consensus to nonconsensus and back to the consensus as the delay increases. Simulation examples are provided to demonstrate the theoretical analysis.

Observer-Based Fixed-Time Secure Tracking Consensus for Networked High-Order Multiagent Systems Against DoS Attacks

Abstract: This article studies the secure tracking consensus problem of nonlinear multiagent systems (MASs) against denial-of-service (DoS) attacks. Two types of DoS attacks, i.e., connectivity-maintained attacks and connectivity-broken attacks, are considered. The resulting topologies caused by DoS attacks may destabilize the consensus performance of MASs. Especially under connectivity-broken attacks, the connectivity between agents is destroyed. To deal with these difficulties, a novel defense strategy consisting of distributed observation and decentralized control is proposed. First, a distributed fixed-time observer (DFTO) is prepared for the case of connectivity-maintained attacks, which can quickly and accurately estimate the leader's information for each follower. Besides, the adverse impact of DoS attacks is completely eliminated. Furthermore, to cope with the problem arising from connectivity-broken attacks, by using an online algorithm of updating label information, an improved resilient DFTO (RDFTO) is further developed, which can preserve those followers having directed paths from the leader to quickly and accurately estimate the leader's information, without being affected by DoS attacks. The developed DFTO and RDFTO have successfully eliminated or weakened the adverse effects caused by DoS attacks. Subsequently, based on the proposed DFTO/RDFTO with the power integrator technique, a fixed-time controller is finally constructed, which realizes the desired transient performance of consensus tracking in the finite-time interval. The effectiveness of the proposed defense strategy is verified by stability analysis and simulation examples.

A Zeno-Free Self-Triggered Approach to Practical Fixed-Time Consensus Tracking With Input Delay

Abstract: This article considers the practical fixed-time self-triggered consensus tracking problem of delayed multiagent networks (MANs) subject to external disturbances under undirected topology and directed topology. The fixed-time consensus implies that the consensus is reached in a finite time and the convergence time is independent of initial conditions under the nonlinear consensus protocols. A self-triggered control (STC) strategy is developed based on the event-triggered control (ETC) strategy. For the ETC strategy, the nonlinear controllers and the measurement errors are designed based on the hyperbolic tangent function to avoid a nondifferential problem and Zeno behavior. To avoid continuous monitoring, the STC strategy is presented. Furthermore, the minimal interevent interval is strictly positive, which implies that no Zeno behavior occurs in the STC strategy. Finally, a numerical example is presented to verify the availability of the algorithms.

Dynamic Event-Triggered Practical Fixed-Time Consensus for Nonlinear Multiagent Systems

Abstract: A new dynamic event-triggered control (ETC) scheme is proposed to address the practical fixed-time consensus (FTC) problem for multi-agent systems (MASs) with nonlinear dynamics. For the dynamic ETC scheme, the dynamic parameters are taken into account to reduce the number of triggering instants and save limited resources, and the triggering condition is based on a new dynamic variable that is obtained online rather than a constant. Moreover, the consensus of the nonlinear MASs can be obtained in a finite time for any initial conditions by the above-mentioned protocol. Finally, an example of Chua’s circuit is given to demonstrate the feasibility of the proposed control algorithms.

Fixed-time consensus control for multi-agent systems with prescribed performance under matched and mismatched disturbances.

Abstract: The consensus problem is considered for multi-agent systems with disturbances. Three fixed-time prescribed performance methods are proposed to satisfy the transient performance and steady-state performance of multi-agent systems consensus. If the multi-agent systems are affected by matched disturbances, the consensus tracking errors constraints are guaranteed at first. Next, the consensus tracking errors constraints and their change rates constraints are further considered. Moreover, with the help of a fixed-time observer, the consensus tracking errors constraints result is expended to the case of multi-agent systems affected by mismatched disturbances. The proposed methods can provide the satisfactory system performances, including that consensus tracking errors always evolve within predefined bounds, converge to a small closed region containing zero in fixed time and then converge to zero asymptotically. Simulations are provided to verify the effectiveness of the proposed methods.

Fully Distributed Consensus of Switched Heterogeneous Nonlinear Multi-Agent Systems With Bouc-Wen Hysteresis Input

Abstract: This paper studies the adaptive fully distributed consensus problem for a class of nonlinear multi-agent systems (MASs) whose structures are heterogeneous, where agents with first-order dynamics and second-order dynamics exist simultaneously. Moreover, each agent subjects to Bouc-Wen hysteresis input. Due to the changes of the internal and external environment, all agents are considered to possess multiple modes and display the switching characteristic. To achieve the consensus tracking control of the considered MAS, first, the totally unknown nonlinear functions representing the system uncertainties are approximated by utilizing radial basis function neural networks (RBFNNs). Then, an adaptive neural consensus control protocol, which can enable the consensus objective to be achieved for the MAS, is designed via using the fully distributed design scheme and adaptive neural control method. It is noted that the information on the number of agents and the interaction topology is not required during the protocol design. Based on the Lyapunov stability theory, the proposed consensus protocol can ensure all signals of the considered MAS is bounded. Finally, simulation results are presented to show the feasibility and effectiveness of the proposed consensus protocol.

Leader-Following Output Consensus of Heterogeneous Uncertain Linear Multiagent Systems With Dynamic Event-Triggered Strategy

Abstract: This article investigates the leader-following output consensus problem of heterogeneous linear multiagent systems, where the nonidentical followers are subject to norm bounded parameter uncertainties. Two novel distributed event-triggered consensus strategies based on state feedback and output feedback, respectively, are proposed to solve the leader-following output consensus problem. A dynamic event-triggering mechanism which involves internal state variables is proposed to determine the next triggering instant. It should be noted that the controllers can be designed without the knowledge of some global graph information, such as the eigenvalues of the Laplacian matrix associated with the corresponding communication graph and the number of agents. In addition, the interevent time can be prolonged and the Zeno behavior can be excluded with the proposed dynamic triggering mechanism. Finally, an example is presented to illustrate the effectiveness of the proposed controllers.

Finite-Time Consensus Tracking for Incommensurate Fractional-Order Nonlinear Multiagent Systems With Directed Switching Topologies

Abstract: This article investigates the problem of finite-time consensus tracking for incommensurate fractional-order nonlinear multiagent systems (MASs) with general directed switching topology. For the leader with bounded but arbitrary dynamics, a neighborhood-based saturated observer is first designed to guarantee that the observer's state converges to the leader's state in finite time. By utilizing a fuzzy-logic system to approximate the heterogeneous and unmodeled nonlinear dynamics, an observer-based adaptive parameter control protocol is designed to solve the problem of finite-time consensus tracking of incommensurate fractional-order nonlinear MASs on directed switching topology with a restricted dwell time. Then, the derived result is further extended to the case of directed switching topology without a restricted dwell time by designing an observer-based adaptive gain control protocol. By artfully choosing a piecewise Lyapunov function, it is shown that the consensus tracking error converges to a small adjustable residual set in finite time for both the cases with and without a restricted dwell time. It should be noted that the proposed adaptive gain consensus tracking protocol is completely distributed in the sense that there is no need for any global information. The effectiveness of the proposed consensus tracking scheme is illustrated by numerical simulations.

Fuzzy Adaptive Optimal Consensus Fault-Tolerant Control for Stochastic Nonlinear Multiagent Systems

Abstract: This article investigates the problem of adaptive fuzzy optimal distributed consensus control for stochastic multiagent systems (MASs) with full-state constraints and nonaffine nonlinear faults. Fuzzy logic systems are employed to identify the unknown nonlinearities. To solve the problem of optimal state constraint control, a barrier Lyapunov function based optimal cost function is designed. By introducing Butterworth low-pass filter into control design, the deleterious effects raised by nonlinear fault can be compensated. By utilizing adaptive dynamic programming algorithm in critic–actor construction, a fuzzy adaptive distributed optimal consensus fault-tolerant control method is proposed, which can ensure that all signals of the controlled system are semiglobally uniformly ultimately bounded in probability, and outputs of the follower agents keep consensus with the output of leader. In addition, system states are all not exceeded their constrained bound. Finally, simulation results are provided to illustrate the feasibility of the developed control method and theorem.

Resilient Consensus of Multiagent Systems Under Malicious Attacks: Appointed-Time Observer-Based Approach

Abstract: This article aims to establish an appointed-time observer-based framework to efficiently address the resilient consensus control problem of linear multiagent systems with malicious attacks. The local appointed-time state observer is skillfully designed for each agent to estimate the agent's actual state value at the appointed time, even in the presence of unknown malicious attacks. Based on the state estimation, a new kind of resilient control strategy is proposed, where a virtual system is constructed for each agent to generate an ideal state value such that the consensus of normal agents can be achieved with the exchange of ideal state values among neighboring agents. To specify the consensus trajectory while achieving resilient consensus, the leader-follower resilient consensus is further studied, where the leader is assumed to be a trusted agent with a bounded control input. Compared with the existing results on the resilient consensus, the proposed distributed resilient controller design reduces the requirement on communication connectivity significantly, where the allowable communication graph is only assumed to contain a directed spanning tree. To verify the theoretical analysis, numerical simulations are finally provided.

Distributed Adaptive Consensus of Parabolic PDE Agents on Switching Graphs With Relative Output Information

Abstract: This article mainly solves the consensus issue of parabolic partial differential equation (PDE) agents with switching topology by output feedback. A novel edge-based adaptive control protocol is designed to reach consensus under the condition that the switching graphs are always connected at any switching instants. Different from the existing adaptive protocol associated with partial differential dynamics, the proposed adaptive observer-type law relies on the relative output information rather than relative state information. A proper Lyapunov functional is constructed and some important lemmas are used, then a sufficient condition is obtained for the consensus of parabolic PDE agents on switching graphs. Besides, a corollary about the distributed adaptive consensus of parabolic PDE agents on fixed undirected communication networks is given. Finally, the theoretical results are demonstrated by two numerical simulations.