Impulsive Observer-based Leader-following Consensus for Multi-agent Systems

Hu Ran; Peng Shi-guo

doi:10.12052/gdutxb.220155

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Impulsive Observer-based Leader-following Consensus for Multi-agent Systems

更新时间：2026-05-27

- Impulsive Observer-based Leader-following Consensus for Multi-agent Systems
- Vol. 40, Issue 5, Pages: 88-93(2023)
- 作者机构：
  
  广东工业大学自动化学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.220155
  CLC： TP273
- Published：2023
- 稿件说明：
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胡然, 彭世国. 基于脉冲观测器的多智能体系统的领导跟随一致性[J]. 广东工业大学学报, 2023, 40(5): 88-93.

Hu Ran, Peng Shi-guo. Impulsive Observer-based Leader-following Consensus for Multi-agent Systems[J]. 2023, 40(5): 88-93.
胡然, 彭世国. 基于脉冲观测器的多智能体系统的领导跟随一致性[J]. 广东工业大学学报, 2023, 40(5): 88-93. DOI： 10.12052/gdutxb.220155.

Hu Ran, Peng Shi-guo. Impulsive Observer-based Leader-following Consensus for Multi-agent Systems[J]. 2023, 40(5): 88-93. DOI： 10.12052/gdutxb.220155.

摘要

本文研究了只有部分跟随者可获取领导者信息的多智能体系统的领导跟随一致性问题。对于不能获得领导者信息的部分跟随者，需要估计领导者的状态。另外，鉴于在某些条件下只能获得智能体的不连续的输出信息，引入脉冲观测器来减少多智能体系统的采样次数。本文的目的是设计一种基于脉冲观测器的控制器来实现领导跟随多智能体系统的一致性。首先，设计了可以估计领导者状态的分布式脉冲全维观测器以及一致性协议。其次，推导出误差系统的动力学方程，并利用误差变量构造合适的Lyapunov函数。最后，利用Lyapunov稳定性理论结合线性矩阵不等式研究误差系统的稳定性问题，得到多智能体系统领导跟随一致性问题的充分条件，并用数值仿真验证了结果的有效性。

Abstract

In this paper

we investigate the problem of consensus in leader-following multi-agent system

where the information of the leader is only accessed by a subset of the following agents. For the part of the follower who cannot obtain the leader’s information

the state of the leader need to be estimated. In addition

considering the discontinuity of obtaining the output information of agents under certain conditions

an impulsive observer is introduced to reduce the sampling times among multiple agents. To achieve this

this paper aims to design a controller based on impulsive observer to achieve the consensus of leader-following multi-agent systems. Firstly

an impulsive full-order observer and a consensus protocol are designed for each follower

so that the follower can use the observer to estimate the leader. Secondly

the dynamic equation of the error system is derived

and the appropriately Lyapunov function is constructed by using the error variables. Finally

the stability of error systems is studied by using the Lyapunov stability theory combining with the linear matrix inequalities

so that the sufficient conditions for the leader-following consensus problem of multi-agent systems can be obtained. Numerical simulation results clearly show the effectiveness of the proposed controller.

关键词

Keywords

references

ZOU W, ZHOU C, XIANG Z. Sampled-data leader-following consensus of nonlinear multi-agent systems subject to impulsive perturbations [J]. Communications in Nonlinear Science and Numerical Simulation, 2019, 78: 104884.

SHI Y, YIN Y, WANG S, et al . Distributed leader-following consensus of nonlinear multi-agent systems with nonlinear input dynamics [J ] . Neurocomputing, 2018, 286: 193-197.

WANG Y, CHENG Z, XIAO M. UAVs’ formation keeping control based on multi-agent system consensus [J]. IEEE Access, 2020, 8: 49000-49012.

ZHANG Z H, PENG S G. Leader-following consensus of second-order multi-agent systems with switching topology [J]. Journal of Guangdong University of Technology, 2018, 35(2): 75-80.

HU X, ZHANG Z, LI C, et al . Leader-following consensus of multi-agent systems via a hybrid protocol with saturation effects [J ] . International Journal of Control, Automation and Systems, 2021, 19(1): 124-136.

ZHANG Y, LI R, ZHAO W, et al . Stochastic leader-following consensus of multi-agent systems with measurement noises and communication time-delays [J ] . Neurocomputing, 2018, 282: 136-145.

JIANG Y, ZHANG Y, WANG H, et al . Sliding-mode observers based distributed consensus control for nonlinear multi-agent systems with disturbances [J ] . Complex Intelligent Systems, 2022, 8(3): 1889-1897.

HONG Y, CHEN G, BUSHNELL L. Distributed observers design for leader-following control of multi-agent networks [J]. Automatica, 2008, 44(3): 846-850.

RAFF T, ALLGOWER F. An impulsive observer that estimates the exact state of a linear continuous-time system in predetermined finite time[C]//2007 Mediterranean Conference on Control Automation. Athens: IEEE, 2007: 1-3.

WANG Y, LI X. Impulsive observer and impulsive control for timedelay systems [J]. Journal of the Franklin Institute, 2020, 357(13): 8529-8542.

CHEN W H, YANG W, LU X. Impulsive observer-based stabilisation of uncertain linear systems [J]. IET Control Theory Applications, 2014, 8(3): 149-159.

RAO H, LIU F, PENG H, et al . Observer-based impulsive synchronization for neural networks with uncertain exchanging information [J ] . IEEE Transactions on Neural Networks and Learning Systems, 2019, 31(10): 3777-3787.

QIN W, LIU Z, CHEN Z. Impulsive observer-based consensus control for multi-agent systems with time delay [J]. International Journal of Control, 2015, 88(9): 1789-1804.

BOYD S, GHAOUI L, FERON E, et al . Linear matrix inequalities in system and control theory[M ] . Philadelphia:Society for Industrial and Applied Mathematics, 1994.

HORN R A, JOHNSON C R. Matrix analysis[M]. Cambridge:Cambridge University Press, 2012.

MERINO D I. Topics in matrix analysis[M]. Baltimore:The Johns Hopkins University, 1992.

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