Quasi-Consensus of Multi-Agent Systems: Encoding-Decoding Scheme and Parametric Lyapunov Approach

Zhang Tianle; Peng Shiguo; Zhang Haoyang

doi:10.12052/gdutxb.240117

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Quasi-Consensus of Multi-Agent Systems: Encoding-Decoding Scheme and Parametric Lyapunov Approach

更新时间：2026-05-27

- Quasi-Consensus of Multi-Agent Systems: Encoding-Decoding Scheme and Parametric Lyapunov Approach
- Vol. 42, Issue 2, Pages: 89-96(2025)
- 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.240117
  CLC： TP273
- Published：2025
- 稿件说明：
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张添乐, 彭世国, 张浩洋. 编码−解码方案与参量Lyapunov方法下多智能体系统的拟一致性[J]. 广东工业大学学报, 2025, 42(2): 89–96.

Zhang Tianle, Peng Shiguo, Zhang Haoyang. Quasi-Consensus of Multi-Agent Systems: Encoding-Decoding Scheme and Parametric Lyapunov Approach[J]. 2025, 42(2): 89-96.
张添乐, 彭世国, 张浩洋. 编码−解码方案与参量Lyapunov方法下多智能体系统的拟一致性[J]. 广东工业大学学报, 2025, 42(2): 89–96. DOI： 10.12052/gdutxb.240117

Zhang Tianle, Peng Shiguo, Zhang Haoyang. Quasi-Consensus of Multi-Agent Systems: Encoding-Decoding Scheme and Parametric Lyapunov Approach[J]. 2025, 42(2): 89-96. DOI： 10.12052/gdutxb.240117.

摘要

连续控制协议对无线网络通信下多智能体系统的信道要求较高，而且带宽利用率较为低下。为解决上述问题，本文设计了一种更具灵活性的编码−解码方案，并研究了一类线性离散时间受扰多智能体系统的拟一致性问题。所设计的编码−解码方案引入了新的量化变量，使量化器能够更灵活地调节合适的量化间隔。为更贴合实际应用系统，本文同时考虑了系统与编码器均受到外部干扰的情况，使所考虑模型更具一般性。结合Lyapunov稳定性理论，给出了系统实现拟一致性的充分条件，并估量了误差界限的大小与量化器的最大量化水平。这一方法丰富了编码−解码方案下多智能体系统拟一致性理论的应用范围。最后，通过MATLAB数值仿真实例验证了本文结果的有效性。

Abstract

Higher request on wireless network communication channels is required for multi-agent systems with continuous protocol

which lowly utilizes its bandwidth. To address such an issue

a more flexible encoding-decoding scheme is proposed and the quasi-consensus investigated for a class of linear discrete-time perturbed multi-agent systems. The designed encoding-decoding scheme introduces new quantization variables

enabling the quantizer to adjust the appropriate quantization interval more flexibly. Moreover

to better fit practical application systems

the situation where both the system and encoder are subject to external disturbance is considered

making the considered model more general. According to the Lyapunov stability theory

sufficient conditions for achieving quasi-consensus are provided. Furthermore

and the error boundedness and the maximum quantization level of the quantizer are estimated. Finally

a MATLAB simulation example is presented to demonstrate the effectiveness of the results in this paper.

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references

WANG X, SHEN L, LIU Z, et al . Coordinated flight control of miniature fixed-wing UAV swarms: methods and experiments[J ] . Science China Information Sciences, 2019, 62: 1-17.

YAN Z, HAN L, LI X, et al . Event-triggered formation control for time-delayed discrete-time multi-agent system applied to multi-UAV formation flying[J ] . Journal of the Franklin Institute, 2023, 360(5): 3677-3699.

QUAN Y, XI L. Smart generation system: a decentralized multi-agent control architecture based on improved consensus algorithm for generation command dispatch of sustainable energy systems[J]. Applied Energy, 2024, 365: 123209.

ZHANG H Y, PENG S G. A research on the consensus problem of multi-agent systems with random time delays based on model reduction[J]. Journal of Guangdong University of Technology, 2019, 36(2): 86-90.

LIU X, CHEN T. Synchronization analysis for nonlinearly-coupled complex networks with an asymmetrical coupling matrix[J]. Physica A: Statistical Mechanics and its Applications, 2008, 387(16-17): 4429-4439.

HU Z, MU X. Impulsive consensus of stochastic multi-agent systems under semi-Markovian switching topologies and application[J]. Automatica, 2023, 150: 110871.

SAKAGUCHI A, USHIO T. Dynamic pinning consensus control of multi-agent systems[J]. IEEE Control Systems Letters, 2017, 1(2): 340-345.

LIU K, JI Z. Dynamic event-triggered consensus of general linear multi-agent systems with adaptive strategy[J]. IEEE Transactions on Circuits and Systems II: Express Briefs, 2022, 69(8): 3440-3444.

SYED ALI M, AGALYA R, SAROHA S, et al . Leaderless consensus of non-linear mixed delay multi-agent systems with random packet losses via sampled-data control[J ] . International Journal of Control, Automation and Systems, 2020, 18(7): 1885-1893.

WANG K P, TANG Z, PARK J H, et al . Impulsive time window based quasi-consensus on stochastic nonlinear multi-agent systems[J ] . IEEE Transactions on Network Science and Engineering, 2022, 9(5): 3602-3613.

CHEN R, PENG S. Leader-follower quasi-consensus of multi-agent systems with packet loss using event-triggered impulsive control[J]. Mathematics, 2023, 11(13): 2969.

GAO C, WANG Z, HE X, et al . Differentially private consensus control for discrete-time multi-agent systems: encoding-decoding schemes[J ] . IEEE Transactions on Automatic Control, 2024, 69(8): 5554-5561.

GAO C, WANG Z, HE X, et al . Sampled-data-based fault-t olerant consensus control for multi-agent systems: a data privacy preserving scheme[J ] . Automatica, 2021, 133: 109847.

LI H, HUANG C, CHEN G, et al . Distributed consensus optimization in multiagent networks with time-varying directed topologies and quantized communication[J ] . IEEE Transactions on Cybernetics, 2017, 47(8): 2044-2057.

WANG Z, WANG L, LIU S, et al . Encoding-decoding-based control and filtering of networked systems: Insights, developments and opportunities[J ] . IEEE/CAA Journal of Automatica Sinica, 2017, 5(1): 3-18.

LI H, CHEN G, LIAO X, et al . Leader-following consensus of discrete-time multiagent systems with encoding-decoding[J ] . IEEE Transactions on Circuits and Systems II: Express Briefs, 2015, 63(4): 401-405.

GAO C, WANG Z, HE X, et al . Fault-tolerant consensus control for multiagent systems: an encryption-decryption scheme[J ] . IEEE Transactions on Automatic Control, 2021, 67(5): 2560-2567.

JIN Z, GUPTA V, MURRAY R M. State estimation over packet dropping networks using multiple description coding[J]. Automatica, 2006, 42(9): 1441-1452.

ZHOU L, LU G. Detection and stabilization for discrete-time descriptor systems via a limited capacity communication channel[J]. Automatica, 2009, 45(10): 2272-2277.

LI T, FU M, XIE L, et al . Distributed consensus with limited com-munication data rate[J ] . IEEE Transactions on Automatic Control, 2010, 56(2): 279-292.

HE W, QIAN F, LAM J, et al . Quasi-synchronization of hetero- geneous dynamic networks via distributed impulsive control: Error estimation, optimization and design[J ] . Automatica, 2015, 62: 249-26.

Xue M, Tang Y, Ren W, et al . Practical consensus tracking of asynchronously switched multi-agent systems[J ] . IEEE Transactions on Automatic Control, 2024, 69(11): 7758-7772.

ZHU H, LU J, LOU J. Event-triggered impulsive control for nonlinear systems: the control packet loss case[J]. IEEE Transactions on Circuits and Systems II: Express Briefs, 2022, 69(7): 3204-3208.

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