Predefined-Time Non-Disruptive Formation Control for Open Multi-Agent Systems

JIA Zhi’an; CHI Ming; QU Fanrong; XU Jingzhe; LIU Zhiwei

doi:10.12263/DZXB.20251188

您当前的位置：

首页 >

文章列表页 >

Predefined-Time Non-Disruptive Formation Control for Open Multi-Agent Systems

The Theory and Application of Swarm Intelligence Technology in the Information\-Rich Era | 更新时间：2026-06-16

- Predefined-Time Non-Disruptive Formation Control for Open Multi-Agent Systems
- ACTA ELECTRONICA SINICA Vol. 54, Issue 3, Pages: 959-969(2026)
- 作者机构：
  
  华中科技大学人工智能与自动化学院，湖北武汉 430074
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(62525603;62373162;U24A20268;62222205);Fundamental Research Funds for the Central Universities(YCJJ20252327)
- DOI：10.12263/DZXB.20251188
  CLC： TP13;TP273
- Received：09 January 2026，
  
  Accepted：22 January 2026，
  
  Published：25 March 2026
- 稿件说明：
移动端阅览
贾志安, 池明, 曲凡荣, 等. 开放多智能体系统的预定义时间无扰编队控制[J]. 电子学报, 2026, 54(03): 959-969.

JIA Zhi’an, CHI Ming, QU Fanrong, et al. Predefined-Time Non-Disruptive Formation Control for Open Multi-Agent Systems[J]. Acta Electronica Sinica, 2026, 54(03): 959-969.
贾志安, 池明, 曲凡荣, 等. 开放多智能体系统的预定义时间无扰编队控制[J]. 电子学报, 2026, 54(03): 959-969. DOI：10.12263/DZXB.20251188

JIA Zhi’an, CHI Ming, QU Fanrong, et al. Predefined-Time Non-Disruptive Formation Control for Open Multi-Agent Systems[J]. Acta Electronica Sinica, 2026, 54(03): 959-969. DOI：10.12263/DZXB.20251188

摘要

随着智能化与无人系统技术的快速发展，开放多智能体系统（Open Multi-Agent Systems，OMAS）因其能够适应系统成员的动态变化而受到广泛关注。与传统多智能体系统（Multi-Agent Systems，MAS）不同，OMAS允许智能体在运行过程中随机加入或离开系统。这种动态特性在提升系统灵活性的同时，也带来了新的控制挑战：新加入智能体通常具有随机的初始状态，可能破坏原有智能体间的编队稳定性，甚至导致整体系统性能下降。针对上述问题，本文系统研究了OMAS中的预定义时间无扰编队控制问题。首先，明确定义了“无扰编队控制”的概念，其核心在于确保新智能体的加入不会影响原有智能体的编队状态，即原有智能体的跟踪误差在新智能体加入后始终保持为零。在此基础上，本文提出了一种基于信息隔离的双层控制框架。在上层，设计了基于平均子序列缩减的信息隔离算法，用于局部识别并隔离可能引入扰动的智能体状态。具体而言，每个智能体通过对比自身与邻居间的状态偏差，剔除极端值信息，从而有效过滤新加入智能体带来的异常状态影响，确保原有智能体间的协同信息不受干扰。在下层，引入了一种预定义时间控制策略，通过构造时变函数，使所有智能体（包括新加入的智能体）的编队跟踪误差能够在用户预设时间内收敛至零，且收敛时间与系统初始条件无关，有效地保证了新加入的智能体在预定义时间内完成编队控制。为验证所提算法的有效性和优越性，本文进行了数值仿真实验。仿真中设置了智能体随机加入与离开的动态场景，并将所提算法与现有编队控制方法进行了对比。结果表明：本文算法在新智能体加入时，能够完全消除其对原有智能体编队状态的扰动，跟踪误差曲线平滑无波动；同时，新加入智能体可在预设时间内快速、准确地收敛至期望编队位置。相比之下，现有方法在新智能体加入时会引起原有智能体跟踪误差的显著振荡，破坏编队形态，这进一步凸显了本文算法的优越性能。

Abstract

With the rapid development of intelligent and unmanned systems

open multi-agent systems (OMAS) have garnered significant attention due to their ability to adapt to dynamic changes in system membership. Unlike traditional multi-agent systems (MAS)

OMAS allow agents to randomly join or leave during operation. While this dynamic nature enhances system flexibility

it also introduces new control challenges: newly joined agents often possess random initial states

which can disrupt the formation stability among existing agents and even degrade overall system performance. To address these issues

this paper systematically investigates the predefined-time non-disruptive formation control problem in OMAS. First

the concept of “non-disruptive formation control” is clearly defined

with its core objective being to ensure that the joining of new agents does not affect the formation state of the existing agents. Specifically

the tracking errors of the existing agents must remain zero after new agents join. Building upon this

a dual-layer control framework based on information isolation is proposed. The upper layer employs a designed information isolation algorithm based on the mean subsequence reduced method to locally identify and isolate agent states that may introduce disturbances. Concretely

each agent compares its state deviation with its neighbors

discards extreme values

thereby effectively filtering out abnormal state influences from newly joined agents and ensuring that the cooperative information among existing agents remains uncontaminated. The lower layer introduces a predefined-time control strategy. By constructing a time-varying scaling function

the formation tracking errors of all agents

including newly joined ones

converge to zero within a user-defined time

independent of initial conditions. This effectively guarantees that newly joined agents complete formation control within the predefined time. To validate the effectiveness and superiority of the proposed algorithm

numerical simulations are conducted. A dynamic scenario with agents randomly joining and leaving is simulated

and the proposed algorithm is compared with existing formation control methods. The results demonstrate that our algorithm completely eliminates the disturbance to the formation state of existing agents when new agents join

yielding smooth tracking error curves without fluctuations. Simultaneously

newly joined agents can converge to the desired formation position quickly and accurately within the predefined time. In contrast

existing methods cause significant oscillations in the tracking errors of existing agents upon the arrival of new agents

disrupting the formation geometry. This further highlights the superior performance of the proposed algorithm.

关键词

Keywords

references

江碧涛 , 温广辉 , 周佳玲 , 等 . 智能无人集群系统跨域协同技术研究现状与展望 [J ] . 中国工程科学 , 2024 , 26 ( 1 ): 117 - 126 . DOI: 10.15302/j-sscae-2024.01.015 http://dx.doi.org/10.15302/j-sscae-2024.01.015

Jiang Bitao , Wen Guanghui , Zhou Jialing , et al . Cross-domain cooperative technology of intelligent unmanned swarm systems: Current status and prospects [J ] . Strategic Study of CAE , 2024 , 26 ( 1 ): 117 - 126 . (in Chinese) . DOI: 10.15302/j-sscae-2024.01.015 http://dx.doi.org/10.15302/j-sscae-2024.01.015

Cohen K , Leshem A . A time-varying opportunistic approach to lifetime maximization of wireless sensor networks [J ] . IEEE Transactions on Signal Processing , 2010 , 58 ( 10 ): 5307 - 5319 . DOI: 10.1109/tsp.2010.2052459 http://dx.doi.org/10.1109/tsp.2010.2052459

Nouyan S , Campo A , Dorigo M . Path formation in a robot swarm: Self-organized strategies to find your way home [J ] . Swarm Intelligence , 2008 , 2 ( 1 ): 1 - 23 . DOI: 10.1007/s11721-007-0009-6 http://dx.doi.org/10.1007/s11721-007-0009-6

Stüdli S , Yan Yamin , Seron M M , et al . “Plug-and-play” style connection methods for graphs with an application in expanding multiagent consensus networks [J ] . IEEE Transactions on Automatic Control , 2024 , 69 ( 5 ): 2883 - 2898 . DOI: 10.1109/tac.2023.3298256 http://dx.doi.org/10.1109/tac.2023.3298256

Jia Zhian , Chi Ming , Liu Zhiwei , et al . Nondisruptive consensus in discrete-time open multiagent systems with double integrator dynamics [J ] . IEEE Transactions on Automatic Control , 2026 , 71 ( 3 ): 2093 - 2100 . DOI: 10.1109/tac.2025.3621990 http://dx.doi.org/10.1109/tac.2025.3621990

Wang Yujuan , Song Yongduan , Hill D J , et al . Prescribed-time consensus and containment control of networked multiagent systems [J ] . IEEE Transactions on Cybernetics , 2019 , 49 ( 4 ): 1138 - 1147 . DOI: 10.1109/tcyb.2017.2788874 http://dx.doi.org/10.1109/tcyb.2017.2788874

Dai Shijie , Wu Zhengxing , Zhang Pengfei , et al . Distributed formation control for a multirobotic fish system with model-based event-triggered communication mechanism [J ] . IEEE Transactions on Industrial Electronics , 2023 , 70 ( 11 ): 11433 - 11442 . DOI: 10.1109/tie.2022.3232659 http://dx.doi.org/10.1109/tie.2022.3232659

Liang Changduo , Ge Mingfeng , Liu Zhiwei , et al . Predefined-time formation tracking control of networked marine surface vehicles [J ] . Control Engineering Practice , 2021 , 107 : 104682 . DOI: 10.1016/j.conengprac.2020.104682 http://dx.doi.org/10.1016/j.conengprac.2020.104682

Ding Can , Zhang Zhe , Miao Zhiqiang , et al . Event-based finite-time formation tracking control for UAV with bearing measurements [J ] . IEEE Transactions on Industrial Electronics , 2025 , 72 ( 7 ): 7482 - 7492 . DOI: 10.1109/tie.2024.3511141 http://dx.doi.org/10.1109/tie.2024.3511141

Zhao Dan , Lv Yuezu , Yu Xinghuo , et al . Resilient consensus of higher order multiagent networks: An attack isolation-based approach [J ] . IEEE Transactions on Automatic Control , 2022 , 67 ( 2 ): 1001 - 1007 . DOI: 10.1109/tac.2021.3075327 http://dx.doi.org/10.1109/tac.2021.3075327

Wang Tingting , Shi Zhexin , Dong Xiwang , et al . Output affine formation maneuver control for heterogeneous multiagent systems with nonautonomous leaders [J ] . IEEE Transactions on Industrial Electronics , 2025 , 72 ( 5 ): 5376 - 5386 . DOI: 10.1109/tie.2024.3476910 http://dx.doi.org/10.1109/tie.2024.3476910

Ding Tengfei , Ge Mingfeng , Xiong Caihua , et al . Prescribed-time formation tracking of second-order multi-agent networks with directed graphs [J ] . Automatica , 2023 , 152 : 110997 . DOI: 10.1016/j.automatica.2023.110997 http://dx.doi.org/10.1016/j.automatica.2023.110997

Ren Yuanhong , Zhou Wuneng , Li Zhiwei , et al . Prescribed-time cluster lag consensus control for second-order non-linear leader-following multiagent systems [J ] . ISA Transactions , 2021 , 109 : 49 - 60 . DOI: 10.1016/j.isatra.2020.09.012 http://dx.doi.org/10.1016/j.isatra.2020.09.012

Li Jinsheng , Hua Yongzhao , Yu Jianglong , et al . Resilient time-varying formation tracking control for general linear multiagent systems with a nonautonomous leader and adversarial followers [J ] . IEEE Transactions on Cybernetics , 2024 , 54 ( 10 ): 6203 - 6216 . DOI: 10.1109/tcyb.2024.3411092 http://dx.doi.org/10.1109/tcyb.2024.3411092

Zhu Yanzheng , Wang Zuo , Liang Hongjing , et al . Neural-network-based predefined-time adaptive consensus in nonlinear multi-agent systems with switching topologies [J ] . IEEE Transactions on Neural Networks and Learning Systems , 2024 , 35 ( 7 ): 9995 - 10005 . DOI: 10.1109/tnnls.2023.3238336 http://dx.doi.org/10.1109/tnnls.2023.3238336

Zhang Zhuoning , Wu Yongbao , Wang Xiao , et al . Practical prescribed-time consensus of uncertain multi-agent systems via intermittent dynamic event-triggered control [J ] . IEEE Transactions on Circuits and Systems I: Regular Papers , 2025 , 72 ( 11 ): 7358 - 7370 . DOI: 10.1109/tcsi.2025.3568819 http://dx.doi.org/10.1109/tcsi.2025.3568819

Wen Guanghui , Yu Wenwu , Xia Yuanqing , et al . Distributed tracking of nonlinear multiagent systems under directed switching topology: An observer-based protocol [J ] . IEEE Transactions on Systems, Man, and Cybernetics: Systems , 2017 , 47 ( 5 ): 869 - 881 . DOI: 10.1109/tsmc.2016.2564929 http://dx.doi.org/10.1109/tsmc.2016.2564929

Franceschelli M , Frasca P . Proportional dynamic consensus in open multi-agent systems [C ] // 2018 IEEE Conference on Decision and Control (CDC) . Piscataway : IEEE , 2018 : 900 - 905 . DOI: 10.1109/cdc.2018.8619639 http://dx.doi.org/10.1109/cdc.2018.8619639

Hendrickx J M , Rabbat M G . Stability of decentralized gradient descent in open multi-agent systems [C ] // 2020 IEEE 59th Conference on Decision and Control (CDC) . Piscataway : IEEE , 2020 : 4885 - 4890 . DOI: 10.1109/cdc42340.2020.9304049 http://dx.doi.org/10.1109/cdc42340.2020.9304049

de Galland C M , Vizuete R , Hendrickx J M , et al . Random coordinate descent algorithm for open multi-agent systems with complete topology and homogeneous agents [C ] // 2021 60th IEEE Conference on Decision and Control (CDC) . Piscataway : IEEE , 2021 : 1701 - 1708 . DOI: 10.1109/cdc45484.2021.9683049 http://dx.doi.org/10.1109/cdc45484.2021.9683049

Franceschelli M , Frasca P . Stability of open multiagent systems and applications to dynamic consensus [J ] . IEEE Transactions on Automatic Control , 2021 , 66 ( 5 ): 2326 - 2331 . DOI: 10.1109/tac.2020.3009364 http://dx.doi.org/10.1109/tac.2020.3009364

Al Zahra Sanai Dashti Z , Oliva G , Seatzu C , et al . Distributed mode computation in open multi-agent systems [J ] . IEEE Control Systems Letters , 2022 , 6 : 3481 - 3486 . DOI: 10.1109/lcsys.2022.3185419 http://dx.doi.org/10.1109/lcsys.2022.3185419

Oliva G , Franceschelli M , Gasparri A , et al . A sum-of-states preservation framework for open multiagent systems with nonlinear heterogeneous coupling [J ] . IEEE Transactions on Automatic Control , 2024 , 69 ( 3 ): 1991 - 1998 . DOI: 10.1109/tac.2023.3317728 http://dx.doi.org/10.1109/tac.2023.3317728

Liu Yuxuan , Ye Maojiao , Ding Lei , et al . Distributed online resource allocation in open networks [J ] . IEEE Transactions on Automatic Control , 2024 , 69 ( 12 ): 8876 - 8883 . DOI: 10.1109/tac.2024.3419818 http://dx.doi.org/10.1109/tac.2024.3419818

Deplano D , Franceschelli M , Giua A . Stability of paracontractive open multi-agent systems [C ] // 2024 IEEE 63rd Conference on Decision and Control (CDC) . Piscataway : IEEE , 2024 : 3031 - 3036 . DOI: 10.1109/cdc56724.2024.10886676 http://dx.doi.org/10.1109/cdc56724.2024.10886676

Makridis E , Grammenos A , Oliva G , et al . Average consensus over directed networks in open multi-agent systems with acknowledgement feedback [C ] // 2024 IEEE 63rd Conference on Decision and Control (CDC) . Piscataway : IEEE , 2024 : 3051 - 3056 . DOI: 10.1109/cdc56724.2024.10886692 http://dx.doi.org/10.1109/cdc56724.2024.10886692

Xue Mengqi , Tang Yang , Ren Wei , et al . Stability of multi-dimensional switched systems with an application to open multi-agent systems [J ] . Automatica , 2022 , 146 : 110644 . DOI: 10.1016/j.automatica.2022.110644 http://dx.doi.org/10.1016/j.automatica.2022.110644

Chen Shuting , Wan Ying , Cao Jinde . Adaptive Nash equilibrium seeking in hybrid heterogeneous open multi-agent systems under DoS attacks [J ] . IEEE Transactions on Network Science and Engineering , 2025 , 12 ( 4 ): 2770 - 2782 . DOI: 10.1109/tnse.2025.3553900 http://dx.doi.org/10.1109/tnse.2025.3553900

Li Xiaodong , Wen Guanghui , Lv Yuezu , et al . Output consensus tracking of heterogeneous open multiagent systems under actuator attacks [J ] . IEEE Transactions on Control of Network Systems , 2026 , 13 ( 1 ): 423 - 435 . DOI: 10.1109/tcns.2025.3648473 http://dx.doi.org/10.1109/tcns.2025.3648473

LeBlanc H J , Zhang Haotian , Koutsoukos X , et al . Resilient asymptotic consensus in robust networks [J ] . IEEE Journal on Selected Areas in Communications , 2013 , 31 ( 4 ): 766 - 781 . DOI: 10.1109/jsac.2013.130413 http://dx.doi.org/10.1109/jsac.2013.130413

Dibaji S M , Ishii H . Resilient consensus of second-order agent networks: Asynchronous update rules with delays [J ] . Automatica , 2017 , 81 : 123 - 132 . DOI: 10.1016/j.automatica.2017.03.008 http://dx.doi.org/10.1016/j.automatica.2017.03.008

Saldaña D , Prorok A , Sundaram S , et al . Resilient consensus for time-varying networks of dynamic agents [C ] // 2017 American Control Conference (ACC) . Piscataway : IEEE , 2017 : 252 - 258 . DOI: 10.23919/acc.2017.7962962 http://dx.doi.org/10.23919/acc.2017.7962962

Tang Yuanyi , Lv Yuezu , Zhou Jialing , et al . Resilient consensus in open multi-agent systems [J ] . IEEE Control Systems Letters , 2025 , 9 : 1261 - 1266 . DOI: 10.1109/lcsys.2025.3580518 http://dx.doi.org/10.1109/lcsys.2025.3580518

Gu Zhou , Yin Tingting , Lu Qing , et al . Resilient event-triggered formation control and secure estimation of multi-UAV systems [J ] . IEEE Transactions on Industrial Informatics , 2025 , 21 ( 6 ): 4915 - 4923 . DOI: 10.1109/tii.2025.3547012 http://dx.doi.org/10.1109/tii.2025.3547012

Zhang Hongwei , Li Zhongkui , Qu Zhihua , et al . On constructing Lyapunov functions for multi-agent systems [J ] . Automatica , 2015 , 58 : 39 - 42 . DOI: 10.1016/j.automatica.2015.05.006 http://dx.doi.org/10.1016/j.automatica.2015.05.006

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Anti-Disturbance Fixed-Time Formation Control of Multi-Mobile Robots via Event-Triggered Mechanism

Formation Control for Car-Like Mobile Robots Under Slip Conditions

A Reinforcement Learning-Based Framework for Memory Layout Optimization in Ubiquitous Operating Systems

A Review of Techniques for Bypassing Censorship in Encrypted Tunnels and Traffic Analysis

Improved Differential Meet-in-the-Middle Attack against Cipher SIMECK

Related Author

JIA Zhian

WANG Jian-an

YAN Hui-xian

ZHAO Zhi-cheng

WANG Bao-fang

ZHANG Rui-lei

GUO Jian

CHEN Qing-wei

Related Institution

College of Electronics Information Engineering， Taiyuan University of Science and Technology

Shanxi Key Laboratory of Advanced Control and Equipment Intelligence

School of Automation, Nanjing University of Science and Technology

⁰