Leader-following Multi-agent Systems Research Articles

Data-driven output consensus for a class of discrete-time multiagent systems by reinforcement learning techniques

The primary objective of this research paper is to examine the challenges associated with optimization and tracking control in discrete-time multiagent systems. This study begins by defining the optimal tracking control issue within the framework of a leader–follower multiagent system. A novel approach based on policy iteration is introduced for calculating the control law and performance index. The paper also includes an analysis of the convergence properties of this technique, ensuring its effectiveness in reaching optimal solutions. To facilitate this, an actor–critic neural network framework is utilized to approximate the control law and iterative performance index function. The proposed approach enables the real-time implementation of the policy iteration method, eliminating the requirement for prior knowledge of the system’s dynamics. The paper concludes with a series of simulation experiments that demonstrate the practicality and efficiency of the developed optimal tracking control strategies.

Adaptive impulsive consensus of nonlinear multi-agent systems via a distributed self-triggered strategy

This article investigates the consensus problem of nonlinear leader-following multi-agent systems (MASs) via adaptive impulsive control. A distributed impulsive controller is employed, in which an adaptive updating law in the discrete-time setting is designed for the impulsive gain. Moreover, in order to reduce the communication cost, a distributed self-triggered strategy is proposed to determine when the impulsive instant occurs. Some criteria are derived to guarantee consensus of leader-following MASs based on Lyapunov stability theory and algebraic Riccati equation. It is proved that the self-triggered impulsive sequence does not exhibit Zeno behaviour. Finally, an illustrative example is presented to empirically validate the effectiveness of the theoretical results.

On topological conditions for enabling transient control in leader–follower networks

We derive necessary and sufficient conditions for leader–follower multi-agent systems such that we can further apply prescribed performance control to achieve the desired formation while satisfying certain transient constraints. A leader–follower framework is considered in the sense that a group of agents with external inputs are selected as leaders in order to drive the group of followers in a way that the entire system can achieve target formation within certain prescribed performance transient bounds. We first derive necessary conditions on the leader–follower graph topology under which the target formation together with the prescribed performance guarantees can be fulfilled. Afterwards, the derived necessary conditions are extended to necessary and sufficient conditions for leader–follower formation control under transient constraints. Finally, the proposed results are illustrated with simulation examples.

Formation tracking control with disturbance rejection in leader-follower multi-agent systems under dynamic event-triggered mechanism

This paper investigates the problem of time-varying formation tracking (TVFT) in a linear multi-agent systems (MASs) with external disturbance in a type of directed network topology, and proposes a formation control strategy in a leader-follower control framework with disturbance rejection under a dynamic event-triggering mechanism (DETM). Firstly, in order to improve the overall performance of the system, an extended state observer is used to estimate the status of the follower and the presence of external disturbance in real time. Secondly, a DETM is designed to avoid continuous communication between adjacent intelligent agents. And the formation tracking error between adjacent multi-agents is used to formulate a distributed TVFT control strategy. Furthermore, a compensation function is designed to actively offset the impact of time-varying disturbances on system. A Lyapunov function is then established for stability analysis, verifying the absence of Zeno behavior with this DETM. Finally, a comparative numerical simulation was conducted using an unmanned aerial vehicle (UAV) cluster case to verify that the proposed method can save communication resources to a greater extent and has good control performance.

Event-triggered finite-time formation tracking of multi-agent systems with mismatched disturbances under switching topologies

The formation tracking of the leader–follower multi-agent systems (MASs) under switching topologies is investigated. The considered system is exposed to both the mismatched and matched disturbances in the dynamics of the leader and followers, which places higher requirements for the robustness of the control protocol. In the presence of disturbances and leader’s unknown control input, an innovative distributed observer embedded with robust terms is designed firstly to estimate leader’s states in finite time. Taking account of the switching topologies, a novel analysis scheme that divides the convergence process into two stages is proposed to establish the finite-time (FT) convergence of estimation errors. Then, by virtue of a constructed auxiliary variable, a FT controller with an event-triggered mechanism is put forward, in which multiple robust feedback terms are designed wisely to suppress the mismatched and matched disturbances effectively. As a result, the FT formation tracking can be achieved with saved resources, despite perturbed environments and switching topologies. Simulation examples are presented to confirm the effectiveness of the proposed algorithm.

Event-Triggered Cluster Consensus of Multi-Agent Systems via a Modified Genetic Algorithm.

This article is concerned with the event-triggered output feedback cluster consensus of leader-following multi-agent systems (MASs) under limited communication resources. Specifically, the distributed agents are divided into several clusters to accomplish different collective tasks under diverse intracluster and intercluster communications. First, to alleviate excessive communication resource consumption, two sampled-data-based event-triggered schemes are developed to distinguish agent-to-agent communications within clusters and between clusters. Based on these schemes, an event-based cluster consensus control protocol is proposed to solve the problem. Then, sufficient criteria on asymptotic stability of the resulting closed-loop system are derived and expressed in terms of matrix inequalities. It is noteworthy that the derived criteria for controller design are nonlinear and nonconvex with respect to the output feedback control gains and triggering parameters. To handle this issue, a modified genetic algorithm (MGA) with multiple subpopulations is proposed, where the subpopulations are independent of each other. The key feature of the designed MGA lies in that the fitness value is described as an accumulation of initial value and weighing value of each matrix inequality. Finally, an application of satellite formation flying is exemplified to demonstrate the effectiveness of the derived theoretical results.

Integrated fault estimation and control for multi-agent systems with external disturbance using delayed relative information

This paper is dedicated to the problem of actuator fault estimation and fault-tolerant control for general linear leader–follower multi-agent systems subject to external disturbance and communication delay. First, the intermediate variable observer is constructed to estimate faults using relative information with symmetric time delays. A contradiction between the convergence speed of estimation error and the time-delay margin is revealed, where quick convergence implies small time-delay margin. As such, the augmented system observer is employed to improve the convergence speed. In the next, integrated scheme is adopted to handle the bi-directional interaction between fault estimation and fault-tolerant control arising from external disturbance and time-varying faults. In addition, we also consider the asymmetric delay case with only transmission delay. The delay-independent stability condition is derived with the use of augmented system observer by virtue of Lyapunov–Krasovskii function and [Formula: see text] robust theories. Finally, the simulation results are presented to verify the effectiveness of proposed method.

Event-Triggered Control of Lag Consensus for Leader-Following Multi-agent Systems with Nonlinear Dynamics

Event-Triggered Control of Lag Consensus for Leader-Following Multi-agent Systems with Nonlinear Dynamics

Distributed Adaptive Tracking Control of Hidden Leader-Follower Multi-Agent Systems with Unknown Parameters

The distributed leader-follower control of multi-agent systems is discussed. Each agent is expressed in a discrete-time and non-linear dynamic model with an unknown parameter and can be affected by its neighbors’ history information. For each agent, to identify the parameter, one switching set of the parameter estimates is constructed and the optimal parameter estimate is chosen based on the index switching function. Using the given desired reference signal, the leader agent’s control law is designed, and relying on the neighbors’ history information, each follower agent’s local control law is designed. With the designed distributed tracking adaptive control laws, the whole system tracks the given desired reference signal, and in the face of strong couplings the closed-loop system ultimately reaches an agreement. Finally, by comparing simulations of the control strategy with a normal projection algorithm, the results indicate that the adaptive control method with a switching set of the parameter estimates is effective in improving the control performance.

Bipartite Formation Control of Nonlinear Multi-Agent Systems with Fixed and Switching Topologies under Aperiodic DoS Attacks

This paper concentrates on bipartite formation control for nonlinear leader-following multi-agent systems (MASs) with fixed and switching topologies under aperiodic Denial-of-Service (DoS) attacks. Firstly, distributed control protocols are proposed under the aperiodic DoS attacks based on fixed and switching topologies. Then, considering control gains, as well as attack frequency and attack length ratio of the aperiodic DoS attacks, using algebraic graph theory and the Lyapunov stability method, some criteria are acquired to ensure that the nonlinear leader-following MASs with either fixed or switching topologies can realize bipartite formation under aperiodic DoS attacks. Finally, numerical simulations are carried out to validate the correctness of the theoretical results.

Stabilisation of multi-agent systems over finite fields based on high-order fully actuated system approaches

In this paper, the controllability of multi-agent systems over finite fields is studied based on the high-order fully actuated (HOFA) system approaches. The concept of HOFA systems over finite fields is introduced. Necessary and sufficient conditions for the controllability of linear systems over finite fields are established. It is proved that a leader–follower multi-agent system over finite fields is controllable if and only if it can be transformed into an HOFA system. Then the stabilisation control protocol is proposed based on the full-actuation property, and the upper bound of settling time for the system can be determined. The uncontrollable leader–follower multi-agent system over finite fields can be transformed into a controllable subsystem and an autonomous subsystem via structural decomposition, the conditions for the system to be stabilisable are provided. Finally, an illustrative example is shown to verify the validity of the main results of this paper.

Failure-distribution-dependent leader-following fault-tolerant consensus for multiagent system with cyberattacks

This article concentrates on a failure-distribution-dependent leader-following fault-tolerant consensus control for multiagent systems with cyberattacks. First, considering the characteristic of failures, a failure distribution model which is more in line with the actual situation is established. To reduce the influence of zero initial conditions, an [Formula: see text] performance index suitable for leader-following multiagent systems is constructed. After this, it is difficult to obtain the augmented form of the closed-loop system due to the coupling of parameters caused by cyberattacks. Thus, based on the provided failure model and performance index, a new fault-tolerant controller is designed by using topological structure segmentation to satisfy the leader-following multiagent system fault-tolerant consensus. Finally, a numerical example is shown to prove the feasibility of this algorithm.

Distributed Event-Triggered Control for Power Sharing in Grid-Connected AC Microgrid

The traditional communication method will bring a heavy burden to the grid system in the distributed collaborative control of microgrids. In grid-connected ac microgrid, this paper adopts an event-triggered control method to resolve the power sharing problem and reduce the communication cost. To begin, the problem is stated as the control problem of a leader-follower multiagent system and uses a distributed hierarchical control strategy to solve it. The primary controller uses the internal model principle to control the voltage output. To optimize the secondary controller, this paper not only adopts an event-triggered control strategy for the microgrid based on the Lyapunov principle to control the output of the compensator state, but also carries out relevant theoretical verification and analysis to ensure that each agent can exclude Zeno behavior. Finally, simulation instances are used to verify the usefulness of the studied control algorithm.

Distributed Iterative Learning Control of Nonlinear Multiagent Systems Using Controller-Based Dynamic Linearization Method.

When applied to the consensus tracking of repetitive leader-follower multiagent systems (MASs), most of existing distributed iterative learning control (DILC) methods assume that the dynamics of agents are exactly known or up to the affine form. In this article, we study a more general case where the dynamics of agents are unknown, nonlinear, nonaffine, and heterogeneous, and the communication topologies can be iteration-varying. More specifically, we first apply the controller-based dynamic linearization method in the iteration domain to obtain a parametric learning controller using only the local input-output data collected from neighboring agents in a directed graph, and then propose a data-driven distributed adaptive iterative learning control (DAILC) method through the parameter-adaptive learning methods. We show that for each time instant, the tracking error is ultimately bounded in the iteration domain for both of the cases with iteration-invariant and iteration-varying communication topologies. The simulation results show that the proposed DAILC method has faster convergence speed, higher tracking accuracy, and more robust learning and tracking in comparison with a typical DAILC method.

Adaptive Dynamic Event-Triggered Distributed Output Observer for Leader-Follower Multiagent Systems Under Directed Graphs.

Leader-follower consensus problem for multiagent systems (MASs) is an important research hotspot. However, the existing methods take the leader system matrix as a priori knowledge for each agent to design the controller and use the leader's state information. In fact, only the output information may be available in some practical applications. On this basis, this article first designs a novel adaptive distributed dynamic event-triggered observer for each follower to learn the minimum polynomial coefficients of the leader system matrix instead of the leader system matrix. The proposed method is scalable and suitable for large-scale MASs and can reduce the information transmission dimension in observer design. Then, an adaptive dynamic event-triggered compensator based on the observer and leader output information is designed for each follower, thereby solving the leader-follower consensus problem. Finally, several simulation examples are given to verify the effectiveness of the proposed scheme.

Dynamic memory-event-triggered consensus of uncertain MASs with networked attacks and delays

This paper addresses the problem of achieving consensus in leader-following multi-agent systems under event-triggered control, with considerations of model uncertainties, network time-delay, and random deception attacks. To address the challenges of limited network resources, we propose a novel event-triggered control scheme that employs a dynamic memory-based approach. The proposed scheme utilizes multiple historic event-triggered states that are correlated with the states of neighboring agents and the leader, and the threshold parameter varies dynamically with time. We establish a memory-based closed-loop system that considers both network delays and deception attacks. Using the Lyapunov stability theory, a sufficient condition is derived to ensure consensus performance, and the desired controller gains and triggered matrices are obtained by solving linear matrix inequalities. Besides, we provide a comparative analysis of the memoryless dynamic event-triggered control. Finally, we validate the effectiveness of proposed approach with simulation results.

Consensus of Discrete-Time Leader-Following Linear Multi-Agent Systems Under Lyapunov-Function-Based Event-Triggered Mechanism

A novel Lyapunov-function-based event-triggered mechanism (ETM) for discrete-time linear leader-following multi-agent systems is proposed in this brief. Based on the constructed ETM, sufficient conditions to reach leader-following consensus asymptotically or exponentially are derived. Compared with the current results, the Lyapunov function no longer needs to be strictly monotonic decreasing under the designed ETM, which increases the triggering interval. The expected convergence rate can be achieved by the tunable parameters in the ETM. Particularly, the non-triviality of the introduced ETM is proved for some of the degraded systems. Finally, the obtained results are verified by a numerical example.

Adaptive Finite-Time Consensus for Stochastic Multiagent Systems With Uncertain Actuator Faults

This paper aims to develop fully distributed adaptive protocols and establish the finite-time consensus criteria for nonlinear stochastic multi-agent systems that are subjected to serious multiple uncertainties not only in the agents' states and inherent nonlinearities but also in their actuators. Firstly, we propose a new continuous fully distributed consensus protocol for leaderless stochastic multi-agent systems by leveraging the adaptive technology, enabling the agents to achieve the finite-time consensus in probability efficiently. Secondly, we develop an adaptive protocol for leader-following multi-agent systems, and remarkably our protocol contains only one dynamic gain, which is adequate to resist serious multiple uncertainties and to ensure the realization of finite-time consensus in probability. Finally, we provide numerical simulations to verify the effectiveness of our protocols.

Controllability of Leader-following Multi-agent Systems

In this work, the controllability of a class of multi-agent linear systems that are interconnected via communication channels is studied. Condition for controllability have been presented and described in terms of the topology of the followers agents, in the case where the followers agents have the same linear dynamics.

Attack-free protocols design for leader-following consensus of discrete-time multi-agent systems with multiple input delays

The consensus problem for leader-following multi-agent systems (MASs) characterised by discrete-time multiple input delays linear systems with directed communication topologies is investigated. Under reasonable assumptions, full-order observer-based output feedback protocols are first established by using the relative outputs and inputs of neighbouring agents. In order to overcome the impact of potential network attacks, we truncate the relative inputs of the proposed protocols, namely the exchange of communication information between neighbouring agents is forbidden, so that the closed-loop leader-following MAS is inherently immune to being attacked and achieves consensus. Additionally, the improved attack-free protocols not only allow arbitrarily large yet bounded delays, but also only relative output measurement can be available, which reduces the communication burden and thus are easy to implement in practice. A numerical example is worked out to illustrate the effectiveness of the proposed approach.