Consensus Algorithm For Multi-agent Systems Research Articles

A Predefined-Time Consensus Algorithm of Multi-Agent System for Distributed Constrained Optimization

A Predefined-Time Consensus Algorithm of Multi-Agent System for Distributed Constrained Optimization

Consensus Algorithm for Multiagent Systems With Nonuniform Communication Delays and Its Application to Nonholonomic Robot Rendezvous

Consensus Algorithm for Multiagent Systems With Nonuniform Communication Delays and Its Application to Nonholonomic Robot Rendezvous

Distributed constrained finite-time consensus algorithm for second-order multi-agent systems

This paper considers the constrained finite-time consensus control problem for second-order multi-agent systems with leaderless and leader–follower. By using the saturated controller design method and homogenous system theory, a finite-time consensus algorithm for multi-agent systems is proposed. Compared with the existing results, the proposed consensus algorithm makes the closed-loop system not only finite-time convergence but also satisfies the velocity constraints and input saturations. Simulation examples show the effectiveness of the proposed consensus algorithms.

Model-Free Event-Triggered Consensus Algorithm for Multiagent Systems Using Reinforcement Learning Method

In this article, we study the consensus issues of multiagent systems (MASs) without any information of the system model by using the reinforcement learning (RL) method and event-based control strategy. First, we design an adaptive event-based consensus control protocol using the local sampled state information so that the consensus errors of all agents are uniformly ultimately bounded. The validity of the above event-triggered adaptive control protocol is confirmed by excluding the Zeno behavior within finite time. Then, based on the RL approach, we present a model-free algorithm to get the feedback gain matrix, and accomplish constructing the adaptive event-triggered control strategy without the knowledge of model information. Distinct with the existing related works, this RL-based event-triggered adaptive control algorithm only relies on the local sampled state information, irrelevant to any model information or global network information. Finally, we provide some examples to demonstrate the validity of the above adaptive event-based consensus algorithm.

Distributed Finite-Time Consensus Algorithm for Multiagent Systems via Aperiodically Intermittent Protocol

This brief focuses on the dynamic finite-time consensus (FTC) problem of linear multiagent systems (MASs) via distributed intermittent control under directed topology. Firstly, a new neighbor-based intermittent control algorithm is formulated for the MASs, which guarantees all agents can achieve consensus in finite time. Secondly, most of existing works about FTC algorithm is based on the continuous communication. However, in practice, we need to consider the consensus problem under discontinuous communication. Aimed at filling the research gap, the intermittent control FTC algorithm is proposed and results in less communication energy among agents. In addition, it is proved that increasing coupling weight among agents will be an effective method to improve the convergence rate of the considered MASs. Finally, simulation is performed to validate the effectiveness of the proposed scheme.

On the Role of Matrix-Weights Elements in Consensus Algorithms for Multi-Agent Systems

This paper examines the roles of the matrix weight elements in matrix-weighted consensus. The consensus algorithms dictate that all agents reach consensus when the weighted graph is connected. However, it is not always the case for matrix weighted graphs. The conditions leading to different types of consensus have been extensively analysed based on the properties of matrix-weighted Laplacians and graph theoretic methods. However, in practice, there is concern on how to pick matrix-weights to achieve some desired consensus, or how the change of elements in matrix weights affects the consensus algorithm. By selecting the elements in the matrix weights, different clusters may be possible. In this paper, we map the roles of the elements of the matrix weights in the systems consensus algorithm. We explore the choice of matrix weights to achieve different types of consensus and clustering. Our results are demonstrated on a network of three agents where each agent has three states.

A class of distributed event-triggered average consensus algorithms for multi-agent systems

This paper proposes a class of distributed event-triggered algorithms that solve the average consensus problem in multi-agent systems. By designing events such that a specifically chosen Lyapunov function is monotonically decreasing, event-triggered algorithms succeed in reducing communications among agents while still ensuring that the entire system converges to the desired state. However, depending on the chosen Lyapunov function the transient behaviours can be very different. Moreover, performance requirements also vary from application to application. Consequently, we are instead interested in considering a class of Lyapunov functions such that each Lyapunov function produces a different event-triggered coordination algorithm to solve the multi-agent average consensus problem. The proposed class of algorithms all guarantee exponential convergence of the resulting system and exclusion of Zeno behaviours. This allows us to easily implement different algorithms that all guarantee correctness to meet varying performance needs. We show that our findings can be applied to the practical clock synchronisation problem in wireless sensor networks (WSNs) and further corroborate their effectiveness with simulation results.

Observer-based Distributed Consensus Algorithm for Multi-agent Systems with Output Saturations

Observer-based Distributed Consensus Algorithm for Multi-agent Systems with Output Saturations

Predefined-Time Consensus of Nonlinear First-Order Systems Using a Time Base Generator

This paper proposes a couple of consensus algorithms for multiagent systems in which agents have first-order nonlinear dynamics, reaching the consensus state at a predefined time independently of the initial conditions. The proposed consensus protocols are based on the so-called time base generators (TBGs), which are time-dependent functions used to build time-varying control laws. Predefined-time convergence to the consensus is proved for connected undirected communication topologies and directed topologies having a spanning tree. Furthermore, one of the proposed protocols is based on the super-twisting controller, providing robustness against disturbances while maintaining the predefined-time convergence property. The performance of the proposed methods is illustrated in simulations, and it is compared with finite-time, fixed-time, and predefined-time consensus protocols. It is shown that the proposed TBG protocols represent an advantage not only in the possibility to define a settling time but also in providing smoother and smaller control actions than existing finite-time, fixed-time, and predefined-time consensus.

Guest editorial: special issue on Consensus‐based Applications in Networked Systems

Guest editorial: special issue on Consensus‐based Applications in Networked Systems

BLDC Multi-Motor Speed Synchronization by Leader Following Multi-Agent and Hybrid Control

In this article, a unique and innovative design for addressing the speed synchronization problem in a multi-motor system using Brush less DC (BLDC), motors is presented by utilizing motor back emf equation and rotor position commonly called sensor less technique. In the proposed method, the system is modelled as a consensus problem of leader following multi-agent system (MAS), and a hybrid controller is designed by using Model Reference Adaptive Control (MRAC) along with Variable Structure (VS) control technique of Sliding Mode Control (SMC), herein called Variable Structure Model Reference Adaptive Control (VS-MRAC). The consensus algorithm of MAS (reformed w.r.t motor speed data), is fused with the hybrid controller to reach consensus on speed regulated by proposed hybrid controller. The stability of a system is endorse by designing a Lyapunov function. The efficiency of the proposed methodology is proven by simulations performed in MATLAB and the acquired results validate the success of proposed design methodology.

Sampling-based event-triggered consensus for multi-agent systems

This work considers the event-based consensus algorithms for multi-agent systems with periodic sampling schemes. An event-triggered consensus algorithm using sampled states are proposed. The measurement error in the event design is defined based on the state of local neighborhood center in order to reduce the number of events. Based on this algorithm, a self-triggered consensus protocol is proposed to further reduce the amount of communication and state sampling, as well as the number of events and thus the controller updates. It is noted that by introducing the periodic sampling scheme, Zeno behaviors can be naturally avoided in both of the algorithms. The effectiveness of the proposed algorithms is illustrated by simulation examples.

Self-triggered consensus of multi-agent systems via model predictive control**This work was supported by the National Natural Science Foundation (No. 61273223), and the National Science Fund for Distinguished Young Scholars of China (No. 61425019).

Abstract This paper proposes a self-triggered consensus algorithm for multi-agent systems by using model predictive control (MPC), where the self-triggering rule and the control algorithm are optimized jointly. The proposed self-triggered MPC consensus algorithm drives the system to reach consensus asymptotically under mild assumptions, if the communication topology is connected. Numerical examples are finally presented to verify the effectiveness and advantages of the self-triggered MPC consensus algorithm. By comparing with the conventional time-triggered and event-triggered consensus algorithms, the self-triggered MPC consensus algorithm is shown to achieve equivalent performance with significant reduction of the numbers of controller updates and information transmission.

Self-Triggered Consensus for Multi-Agent Systems With Zeno-Free Triggers

In this technical note, a self-triggered consensus algorithm for multi-agent systems has been proposed. Each agent receives the state information of its neighbors and computes the average state of its neighborhood. Based on this average state the event trigger is designed to determine when the agent updates its control input and transmits the average state to its neighbors. By specifying a strictly positive minimal inter-event time for each agent, Zeno behavior can be avoided. Then by solving quadratic equations related to the event condition, the self-triggered consensus algorithm is developed by directly computing the event time instants with a set of iterative procedures. It has been proved that with the proposed “Zeno-free” algorithm the agent group can achieve consensus asymptotically. Compared with the existing works, the proposed algorithm is simpler in formulation and computation. Moreover, it has been showed that agents need less time to achieve consensus with considerable reduction of the number of triggering events, controller updates and information transmission. As a result, more energy can be saved using the proposed algorithm in practical multi-agent systems.

A Consensus Algorithm with Buffer in Second-Order Multi-Agent with Time-Varying Delayed Communication

In this paper, we discuss consensus problems for a network of dynamic agents with fixed topologies. A consensus algorithm for multi-agent systems with time-varying delay is presented. With the consideration of the effects of network conditions, such as network-induced delays, packet dropouts, mis-sequence, etc., a communication buffer is introduced for avoiding agents’ communication error, and a method for choosing buffer length is proposed. Using this buffer design, received data is rearranged and transferred in the original order. With the presented consensus algorithm, agents’ consensus is well-performance, and all the agents match the average speed finally. Simulation oriented results verify the effectiveness of the proposed algorithm.

Robust consensus algorithm for multi-agent systems with exogenous disturbances under convergence conditions

In this paper, a robust consensus algorithm is developed and sufficient conditions for convergence to consensus are proposed for a multi-agent system (MAS) with exogenous disturbances subject to partial information. By utilizing H∞ robust control, differential game theory and a design-based approach, the consensus problem of the MAS with exogenous bounded interference is resolved and the disturbances are restrained, simultaneously. Attention is focused on designing an H∞ robust controller (the robust consensus algorithm) based on minimisation of our proposed rational and individual cost functions according to goals of the MAS. Furthermore, sufficient conditions for convergence of the robust consensus algorithm are given. An example is employed to demonstrate that our results are effective and more capable to restrain exogenous disturbances than the existing literature.

Fixed-time Consensus Algorithm for Multi-agent Systems with Integrator Dynamics

The paper addresses the problem of exact average-consensus reaching in a prespecified time. The communication topology is assumed to be defined by a weighted undirected graph and the agents are represented by integrators. A nonlinear control protocol which ensures a finite-time convergence is proposed. With the designed protocol, any a priori specified convergence time can be guaranteed regardless of the initial conditions.

Finite-time consensus algorithm for multi-agent systems with double-integrator dynamics

In this paper, we discuss the finite-time consensus problem for leaderless and leader–follower multi-agent systems with external disturbances. Based on the finite-time control technique, continuous distributed control algorithms are designed for these agents described by double integrators. Firstly, for the leaderless multi-agent systems, it is shown that the states of all agents can reach a consensus in finite time in the absence of disturbances. In the presence of disturbances, the steady-state errors of any two agents can reach a region in finite time. Secondly, for the leader–follower multi-agent systems, finite-time consensus algorithms are also designed based on distributed finite-time observers. Rigorous proof is given by using Lyapunov theory and graph theory. Finally, one example is employed to verify the efficiency of the proposed method.

다 개체 시스템의 상태 일치를 위한 이산 시간 출력 궤환 협조 제어 알고리즘

This paper presents a discrete-time output feedback consensus algorithm for Multi-Agent Systems (MAS). Under the assumption that an agent is aware of the relative state information about its neighbors, a state feedback consensus algorithm is designed based on Linear Matrix Inequality (LMI) method. In general, however, it is possible to obtain its relative output information rather than the relative state information. To reconcile this problem, an Unknown Input Observer (UIO) is employed in this paper. To this end, first it is shown that the relative state information can be estimated using the UIO and the measured relative output information. Then a certainty-equivalence type output feedback consensus algorithm is proposed by combining the LMI-based state feedback consensus algorithm with the UIO. Finally, simulation results are given to illustrate that the proposed method successfully achieves the state consensus.

Connectivity-Preserving Consensus Algorithms for Multi-agent Systems

AbstractThe consensus problem for multi-agent systems with double integrator dynamics is considered in this paper. We propose and analyze a connectivity-preserving consensus algorithm with position measurements only. Under the assumption that the initial interaction network is connected, the connectivity of the interaction network during the dynamical evolution can be preserved. Moreover, the consensus algorithm with a virtual leader is investigated. It is shown that all the agents can asymptotically attain a desired position and velocity even if only one agent in the team has access to the information of the virtual leader. Numerical simulations illustrate the effectiveness of the proposed methods.