开放多智能体系统的预定义时间无扰编队控制

贾志安; 池明; 曲凡荣; 徐景喆; 刘智伟

doi:10.12263/DZXB.20251188

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开放多智能体系统的预定义时间无扰编队控制

信息丰富时代的群体智能理论与技术 | 更新时间：2026-06-16

- 开放多智能体系统的预定义时间无扰编队控制
- Predefined-Time Non-Disruptive Formation Control for Open Multi-Agent Systems
- 电子学报 2026年54卷第3期页码：959-969
- 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：
  
  贾志安男，1998年4月生，河北邯郸人。现为华中科技大学人工智能与自动化学院博士研究生。主要研究方向为开放多智能体系统的协同控制与优化。 E-mail: jiazhian@hust.edu.cn
  池明男，1986年8月生，湖北安陆人。2013年于华中科技大学获得博士学位，现为华中科技大学人工智能与自动化学院教授、博士生导师。主要研究方向为网络控制系统、多智能体系统、复杂网络和混合控制系统。 E-mail: chiming@hust.edu.cn
  曲凡荣女，1996年11月生，河南南阳人。现为华中科技大学人工智能与自动化学院博士研究生。主要研究方向为多智能体系统控制。 E-mail: frqu@hust.edu.cn
  徐景喆男，1997年4月生，浙江嘉兴人。现为华中科技大学人工智能与自动化学院博士研究生。主要研究方向为多智能体系统、分布式控制和分布式优化。 E-mail: jzxu@hust.edu.cn
  刘智伟男，1982年10月生，江西宜春人。2011年于华中科技大学获得博士学位，现为华中科技大学人工智能与自动化学院教授、博士生导师。主要研究方向为分布式网络系统的协同控制与优化。 E-mail: zwliu@hust.edu.cn
- 基金信息：
  
  国家自然科学基金(62525603;62373162;U24A20268;62222205);中央高校基本科研业务费(YCJJ20252327)
- DOI：10.12263/DZXB.20251188
  中图分类号： TP13;TP273
- 收稿：2026-01-09，
  
  录用：2026-01-22，
  
  纸质出版：2026-03-25
- 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

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