Leader-following Consensus Of Multi-agent Systems Research Articles

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.

Leader-Following Consensus of Multi-Agent Systems via Fully Distributed Event-Based Control

Leader-Following Consensus of Multi-Agent Systems via Fully Distributed Event-Based Control

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

Hybrid dynamic event-triggered leader-following consensus for multi-agent systems with external disturbances

Herein, we address the leader-following consensus for multi-agent systems with a directed graph while considering external disturbances. To optimize resource utilization, we propose a hybrid dynamic event-triggered mechanism (HDETM) that minimizes the inter-agent communication and reduces the frequency of controller updates. Furthermore, regularization techniques are employed to ensure that the considered system maintains a Zeno-free behavior even in the presence of an external disturbance by guaranteeing a strictly positive inter-event time. Additionally, we propose a hybrid system framework incorporating auxiliary variables to depict both flow and jump dynamics. A Lyapunov consensus analysis is performed within this framework to verify finite-gain L2 stability. Finally, we validate the efficacy of the HDETM design method through numerical simulations.

Distributed Fixed-Time Leader-Following Consensus for Multi-Agent Systems: An Event-Triggered Mechanism

In this work, a fixed-time leader-following event-triggered (ET) consensus problem for multi-agent systems (MASs) with external disturbances is investigated. A distributed observer is developed to achieve the estimated state of the leader. By means of the observation information, the consensus error system for multi-agents is reformulated into a tracking error system, wherein individual follower agent aims to track the leader agent. Building upon Lyapunov technology and fixed-time stability theory, a new ET protocol is introduced to mitigate communication wastes. Notably, the proposed controller incorporates a strong robust fixed-time control form with lower complexity, and a reliable dynamic triggering condition also ensures the excellent performance of the system. Rigorous demonstrations underscore the stability and robustness of the ET method, while guaranteeing the avoidance of Zeno behavior. Finally, several numerical simulations are provided to underscore the efficacy of the proposed protocols.

A leader-following consensus of multi-agent systems with actuator saturation and semi-Markov switching topologies

<abstract> <p>The leader-following consensus (LFC) issue was investigated in this paper for multi-agent systems (MASs) subject to actuator saturation with semi-Markov switching topologies (SMST). A new consensus protocol was proposed by using a semi-Markov process to model the switching of network topologies. Compared to the traditional Markov switching topologies, the SMST is more general and practical because the transition rates are time-varying. Using the local sector conditions and a suitable Lyapunov-Krasovskii functional, some sufficient conditions are proposed such that the leader-following mean-square consensus is locally achieved. Based on the derived sufficient conditions, an optimization problem was analyzed to determine the consensus feedback gains and to find a maximal estimate of the domain of consensus attraction (DOCA) of a closed-loop model. Thus, a numerical case was presented to verify the performance of the design method.</p> </abstract>

Topology Switching for Optimal Leader-Following Consensus of Multi-Agent Systems

Topology Switching for Optimal Leader-Following Consensus of Multi-Agent Systems

Bipartite Leader-Following Consensus of Multiagent Systems on Switching Signed Networks Under Deception Attacks and Its Application to Image Communication

Bipartite Leader-Following Consensus of Multiagent Systems on Switching Signed Networks Under Deception Attacks and Its Application to Image Communication

A fully distributed event-Triggered control approach to leader-following consensus of multiagent systems

This paper investigates the leader-following consensus problem for general linear multiagent systems under a fully distributed manner. To avoid using the global information of the communication network, two node-based adaptive parameters are designed and introduced to the fully distributed event-based control law. Such a protocol is more scalable and flexible for large-scaled and complex networked system, such as microgrids or multiple unmanned vehicles. A novel event-triggered rule is presented, and an internal dynamic variable is introduced in it to further cut down the triggering times and save the communication resources. A well-designed Lyapunov function candidate is constructed to not only ensure the convergence of the close-looped systems but also avoid using the eigenvalue of Laplacian matrix in the dynamic variable. Moreover, it is proved that the designed event-triggered conditions can avoid the Zeno behaviour. Finally, a simulation example based on a group of unmanned intelligent vehicle systems is provided to demonstrate the validity of the designed control method.

Topology-based dynamic event-triggered leader-following consensus of multi-agent systems under switching topologies

This paper is devoted to the topology-based dynamic event-triggered leader-following consensus issue of general linear multi-agent systems under switching topological structures. The novel topology-based distributed dynamic event-triggered rule is formed, in which a topology-based dynamic auxiliary variable is introduced to reduce the conservatism and save resources. Under novel triggering rules, topology-based distributed event-triggered controllers are constructed. Different control gains are designed for different topological structures. Compared with existing works, conservatism is further reduced. Then the leader-following consensus is achieved with a global exponential convergence rate. Moreover, the average dwell time method is adopted to relax restrictions on the switching speed of topological structures and an original analytical thought is put forward to rule out the Zeno phenomenon concisely and clearly. Finally, two numerical examples and a realistic mass–spring system are utilized to verify the feasibility and superiority of the proposed theory.

Adaptive Leader-Following Consensus of Multiagent Systems With Unknown Disturbances and Switching Topologies

This brief investigates adaptive consensus of a second-order multi-agent system (MAS) with unknown nonlinear dynamics by using the relative position and velocity measurements. Firstly, for a leader-follower MAS, unknown nonlinear dynamics of a self-active leader and all followers are constructed and described by linearly parameterized models. Secondly, based on relative position and velocity measurements, a fully distributed adaptive control law (ACL) is designed, then a novel control protocol by using the ACL is proposed for each follower. Thirdly, with the help of a common Lyapunov function method, the asymptotical stability of the derived dynamical tracking system and the parameter convergence are analyzed. Finally, the correctness of the adaptive protocol is verified by some numerical simulations.

Control for Nonlinear Fuzzy Time-Delay Multiagent Systems: Two Kinds of Distributed Saturation-Constraint Impulsive Approach

The impulsive consensus problems of nonlinear time-delay multi-agent system under communication constraints are analyzed and investigated in the paper. In view of the limited communication channel, global input saturation constraint is integrated into the design of impulse control protocol. Furthermore, in order to reduce energy consumption and communication cost, two kinds of impulsive control protocols are designed which conclude general impulsive control protocols and event-triggered impulsive control protocols. For event-triggered impulsive control protocols, by setting event decision time at impulse time, this novel consensus control protocols not only decrease communication frequency and energy consumption, but also avoid “Zeno behavior”. Through theoretical derivation, some sufficient conditions that guarantee the leader-following consensus of multi-agent system are presented. In the end, for the sake of explaining the superiority of impulse control combined with event-triggered control strategy in more detail, the simulations of two control methods are given respectively for the same multi-agent system, which can be better compared and explained.

Hybrid-triggered bipartite leader-following consensus for multi-agent systems with controller gain variations

This article aims to analyze the leader-following consensus for multi-agent systems (MASs) in the presence of cooperative and competitive interactions. The primary aim of this article is to design a hybrid-triggered control protocol that ensures the bipartite leader-following consensus of MASs under controller gain variations. By using a Bernoulli random variable, time-triggered and event-triggered controllers are combined to form a hybrid-triggered controller. A structurally balanced graph is deployed to illustrate the cooperative and competitive interaction between neighboring agents. By employing Lyapunov stability theory and utilizing the properties of algebraic graph theory, the sufficient requirements for assuring the bipartite leader-following consensus will be established by means of linear matrix inequalities (LMIs). The derived conditions assure the bipartite consensus of the multi-agent system with same magnitude and opposite sign. Furthermore, the controller gain value can be computed by solving the LMIs. Numerical examples will be delivered to verify the viability of the derived theoretical results.

Disturbance observer-based integral sliding-mode control design for leader-following consensus of multi-agent systems and its application to car-following model

In this manuscript, the memory-based integral sliding-mode control (MBISMC) that depends on a disturbance observer (DOB) is designed for the multi-agent systems (MASs) with mismatched disturbance. To do this, DOB is provided to estimate disturbances, which are included in the controller design procedure. Besides that, an integral-type surface function (ISF) is intended to model the properties of the MASs and DOB. The designed ISF contains not only a state-dependent input matrix but also memory information. To date, the stability properties of the MAS with external disturbances, parameter uncertainties, and MBISMC have not been studied in the literature, which is the primary impetus for this research. Further, an H∞-theory and Lyapunov–Krasovskii functional (LKF) is applied to derive sufficient stability conditions that ensure the global asymptotic consensus of the presented model. Meanwhile, the mismatched disturbances of considered MASs are attenuated effectively by the MBISMC method. In conclusion, three numerical examples are offered to demonstrate the practicality and usefulness of the proposed design techniques.

Distributed global adaptive bipartite consensus of multi-agent systems with signed communication topology structure

This paper focuses on designing a fully distributed adaptive fuzzy bipartite consensus control protocol for unknown nonlinear multi-agent systems with a class of undirected signed graph. Utilizing the fuzzy logical system universal approximator as a compensator to describe the uncertain nonlinear dynamics, a fully distributed adaptive fuzzy control protocol is proposed by means of re-parameterized approach and bounding technique, the global bipartite consensus of leader-following multi-agent systems without using any dynamics of the leader is proven via constructing a new Lyapunov function. The proposed protocol overcomes the drawback of the semi-global consensus in existing literature. Furthermore, as an extension of the former result, a bipartite formation control problem is also solved. Finally, the proposed methods are validated by simulation examples.

Cooperative Control of Uncertain Multiagent Systems via Distributed Gaussian Processes

For single agent systems, probabilistic machine learning techniques such as Gaussian process regression have been shown to be suitable methods for inferring models of unknown nonlinearities, which can be employed to improve the performance of control laws. While this approach can be extended to the cooperative control of multi-agent systems, it leads to a decentralized learning of the unknown nonlinearity, i.e., each agent independently infers a model. However, a decentralized learning approach can potentially lead to poor control performance, since the models of individual agents are often accurate in merely a small region of the state space. In order to overcome this issue, we propose a novel method for the distributed aggregation of Gaussian process models, and extend probabilistic error bounds for Gaussian process regression to the proposed approach. Based on this distributed learning method, we develop a cooperative tracking control law for leader-follower consensus of multi-agent systems with partially unknown, higher-order, control-affine dynamics, and analyze its stability using Lyapunov theory. The effectiveness of the proposed methods is demonstrated in numerical evaluations.

Predefined-Time Bounded Consensus of Multiagent Systems With Unknown Nonlinearity via Distributed Adaptive Fuzzy Control.

This article investigates uniformly predefined-time bounded consensus of leader-following multiagent systems (MASs) with unknown system nonlinearity and external disturbance via distributed adaptive fuzzy control. First, uniformly predefined-time-bounded stability is analyzed and a sufficient condition is derived for the system to achieve semiglobally (globally) uniformly predefined-time-bounded consensus. Therein, the settling time is independent of initial conditions and can be defined in advance. Then, for first-order MASs, distributed adaptive fuzzy controllers are designed by combining neighboring consensus errors to drive all following agents to globally track the leader's state within predefined time. For second-order MASs, by formulating filtered errors, the consensus errors between following agents and the leader are shown to be bounded if the filtered errors are bounded. Furthermore, with the distributed controllers designed based on filtered errors, second-order MASs achieve semiglobally uniformly predefined-time-bounded leader-following consensus. Finally, two numerical examples are simulated, including: 1) a first-order leader-following MAS and 2) a second-order Lagrangian system consisting of single-link manipulators, to demonstrate the performance of the proposed controllers.

Resilient Event-/Self-Triggering Leader-Following Consensus Control of Multiagent Systems Against DoS Attacks

This paper focuses on the problem of resilient leader-following consensus for multi-agent systems (MAS) against denial-of-service (DoS) attacks. Two update strategies based on event/self-triggering are proposed for the control protocols to handle the leader-following consensus in unreliable shared networks. We first propose a dynamic event-triggered communication (DETC) scheme to mitigate unnecessary information transfer through energy-limited and vulnerable networks. Continuous communication between agents can be avoided. DoS attacks are supposed to be aperiodic and asynchronous at different edges. The concept of valid DoS attack interval is introduced, and the frequency and duration of attacks are analyzed. The leader-following consensus can be achieved when there exist DoS attacks using the dynamic event-based control strategy. Then to avoid continuous event detection and save computation resources, a self-triggered communication (STC) function is developed. The next triggering moment is predetermined with the latest received state information. And the Zeno behavior is eliminated for the feasibility of the event/self-triggering scheme. Finally, a simulation is provided to verify the effectiveness of the proposed update strategies and control protocols.

Leader-following consensus of multi-agent systems with connectivity-mixed attacks and actuator/sensor faults

This study investigates the leader-following consensus issue of multi-agent systems subject to simultaneous connectivity-mixed attacks, actuator/sensor faults and disturbances. Connectivity-mixed attacks are remodeled into connectivity-maintained and connectivity-paralyzed topologies in a switched version, and actuator/sensor faults are established with unified incipient-type and abrupt-type characteristics. Then, unknown input observer-based decoupling and estimation are incorporated to achieve unknown state and fault observations with the normalized technique, and the leader-following consensus-based compensation to faults, resilience to attacks and robustness to disturbances are also realized with the neighboring output information and sensor fault estimation through the distributed framework. Criteria of achieving exponential leader-following consensus of multi-agent systems under cyber-physical threats are derived with dual attack frequency and activation rate indicators. Simulation example is conducted to exemplify the validation and merits of the proposed leader-following consensus algorithm.

Leader-follower Consensus of Multi-agent Systems with Saturation Nonlinearities via Delta-operator

In this paper, we propose a leader-follower consensus control method using state feedback gains and servo compensators for multi-agent systems with saturation nonlinearities based on a discrete-time difference state space equation of the delta-operator. The consensus control method is that the leader follows reference inputs and the followers follow states of the leader without using the reference inputs. We point out that the proposed method can be recast as a convex optimization problem subject to linear matrix inequalities (LMIs) in order to increase the convergence speed of the consensus. The method includes results of continuous-time systems as a special case where the sampling period goes to zero. In this paper, we study the continuous-time and the discrete-time systems of multi-agent systems within the framework of a unified approach.