基于观测器的具有非自治领导者的多智能体系统事件触发时变编队跟踪控制

张凯; 王佩君; 史桀绮; 黄廷文

doi:10.16383/j.aas.c260069

基于观测器的具有非自治领导者的多智能体系统事件触发时变编队跟踪控制

doi: 10.16383/j.aas.c260069 cstr: 32138.14.j.aas.c260069

张凯^{1, 2, 3,},
王佩君^4,,
史桀绮^{1, 5,},
黄廷文^3,

1.
南京大学计算机软件新技术全国重点实验室南京 210023
2.
南京大学计算机学院南京 210023
3.
深圳理工大学计算机科学与人工智能学院深圳 518055
4.
安徽师范大学数学与统计学院芜湖 241000
5.
南京大学智能科学与技术学院苏州 215163

基金项目: 教育部基础学科和交叉学科突破计划(JYB2025XDXM118), 国家自然科学基金(62576223, 62373003, 62506153), 安徽省自然科学基金(2508085J010) 资助

详细信息

作者简介:
张凯：南京大学计算机学院博士研究生. 主要研究方向为多智能体系统协同控制和事件触发控制. E-mail: zhangk9903@126.com

王佩君：安徽师范大学数学与统计学院教授. 主要研究方向为多智能体系统协同控制与分布式博弈. E-mail: pjwang@ahnu.edu.cn

史桀绮：南京大学智能科学与技术学院副教授. 主要研究方向为基于人工智能感知的机器人算法. E-mail: isjieqi@nju.edu.cn

黄廷文：深圳理工大学计算机科学与人工智能学院教授. 主要研究方向为多智能体系统, 自适应控制和最优控制. 本文通信作者. E-mail: huangtw2024@163.com

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出版历程
- 收稿日期: 2026-01-26
- 录用日期: 2026-04-12
- 网络出版日期: 2026-09-08
- 刊出日期: 2026-10-25

Observer-based Event-triggered Time-varying Formation Tracking Control for Multi-agent Systems With a Non-autonomous Leader

ZHANG Kai^{1, 2, 3
,},
WANG Pei-Jun^4
,,
SHI Jie-Qi^{1, 5
,},
HUANG Ting-Wen^3
,

1.
State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023
2.
School of Computer Science, Nanjing University, Nanjing 210023
3.
Faculty of Com-puter Science and Artificial Intelligence, Shenzhen University of Advanced Technology, Shenzhen 518055
4.
School of Mathematics and Statistics, Anhui Normal University, Wuhu 241000
5.
School of Intelligence Science and Technology, Nanjing University, Suzhou 215163

Funds: Supported by Fundamental and Interdisciplinary Disciplines Breakthrough Plan of the Ministry of Education of China (JYB2025XDXM118), National Natural Science Foundation of China (62576223, 62373003, 62506153), and Anhui Provincial Natural Science Foundation (2508085J010)

More Information

Author Bio:
ZHANG Kai　Ph.D. candidate at the School of Computer Science, Nanjing University. His research interests include cooperative control of multi-agent systems and event-triggered control

WANG Pei-Jun　Professor at the School of Mathematics and Statistics, Anhui Normal University. His research interests include cooperative control of multi-agent systems and distributed games

SHI Jie-Qi　Associate professor at the School of Intelligence Science and Technology, Nanjing University. Her main research interest is AI-perception-based robot algorithms

HUANG Ting-Wen　Professor at the Faculty of Computer Science and Artificial Intelligence, Shenzhen University of Advanced Technology. His research interests include multi-agent systems, adaptive control, and optimal control. Corresponding author of this paper

摘要

摘要: 针对有向拓扑下含非自治领导者的多智能体系统, 提出一种基于未知输入观测器的分布式动态事件触发控制方法, 以解决其时变编队跟踪问题. 首先, 利用智能体之间的相对输出信息设计未知输入观测器, 以估计智能体之间的相对状态. 在此基础上, 引入动态事件触发机制来确定控制输入的更新时刻, 从而有效降低控制更新频率. 随后, 设计一种时变编队跟踪控制协议, 使得跟随者仅依赖相对输出信息即可实现对非自治领导者的编队跟踪. 通过构造合适的Lyapunov函数, 严格证明了编队跟踪误差的渐近收敛性. 此外, 借助反证法严格排除了芝诺行为. 最后, 数值仿真结果验证了所提方法的有效性.
- 多智能体系统 /
- 时变编队跟踪 /
- 未知输入观测器 /
- 动态事件触发
Abstract: This paper investigates the time-varying formation tracking problem for multi-agent systems under directed topology with a non-autonomous leader. A distributed dynamic event-triggered control method based on an unknown input observer (UIO) is proposed. First, a UIO is designed using the relative output information among agents to estimate their relative states. On this basis, a dynamic event-triggered mechanism is introduced to determine the update instants of the control input, thereby effectively reducing the control update frequency. Subsequently, a time-varying formation tracking control protocol is designed, enabling followers to achieve formation tracking of the non-autonomous leader using only relative output information. By constructing an appropriate Lyapunov function, the asymptotic convergence of the formation tracking error is rigorously proved. Furthermore, the existence of Zeno behavior is rigorously excluded by utilizing a proof by contradiction. Finally, numerical simulation results validate the effectiveness of the proposed method.
- multi-agent systems /
- time-varying formation tracking /
- unknown input observer /
- dynamic event-triggered

HTML全文

图 1 例$ 1 $中通信拓扑$ {\cal{G}} $

Fig. 1 Communication topology $ {\cal{G}} $ in Example $ 1 $

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图 2 编队跟踪轨迹

Fig. 2 The trajectory of formation tracking

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图 3 编队位置误差

Fig. 3 Formation position errors

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图 4 编队速度误差

Fig. 4 Formation velocity errors

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图 5 $ \zeta_i(t) $的时间演化曲线

Fig. 5 Time evolution curves of $ \zeta_i(t) $

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图 6 跟随无人机的触发时刻

Fig. 6 Triggering instants of follower UAVs

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图 7 例$ 2 $中通信拓扑$ {\cal{G}} $

Fig. 7 Communication topology $ {\cal{G}} $ in Example $ 2 $

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图 8 编队位置与速度误差

Fig. 8 Formation position and velocity errors

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图 9 编队摆角与角速度误差

Fig. 9 Formation pendulum angle and angular velocity errors

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图 10 $ \zeta_i(t) $的时间演化曲线

Fig. 10 Time evolution curves of $ \zeta_i(t) $

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图 11 小车的触发时刻

Fig. 11 Triggering instants of vehicles

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表 1 不同参数组合下的触发次数与收敛时间

Table 1 Triggering times and convergence time under different parameter combinations

参数		事件触发次数					$ \\|\delta(t)\\|\leq 0.1 $ 的时间(s)
$ \alpha_k $	$ \beta_k $	1	2	3	4	5	$ \\|\delta(t)\\|\leq 0.1 $ 的时间(s)
0.20	0.20	1620	849	1673	812	837	19.1410
0.30	0.20	2081	1071	2136	1091	1019	18.4320
0.40	0.20	2559	1306	2513	1317	1336	17.4650
0.20	0.30	4233	2460	3923	2283	2358	15.8590
0.20	0.25	2786	1473	2706	1506	1452	16.9520

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