Event-triggered Differential Privacy Protection Tracking Control

Xie Guangqiang; Hu Mingyu; Li Yang

doi:10.12052/gdutxb.240022

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

Event-triggered Differential Privacy Protection Tracking Control

更新时间：2026-05-27

- Event-triggered Differential Privacy Protection Tracking Control
- Vol. 42, Issue 2, Pages: 70-80(2025)
- 作者机构：
  
  广东工业大学计算机学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.240022
  CLC： TP391
- Published：2025
- 稿件说明：
移动端阅览
谢光强, 胡明昱, 李杨. 基于事件触发的多智能体系统差分隐私保护跟踪控制[J]. 广东工业大学学报, 2025, 42(2): 70–80.

Xie Guangqiang, Hu Mingyu, Li Yang. Event-triggered Differential Privacy Protection Tracking Control[J]. 2025, 42(2): 70-80.
谢光强, 胡明昱, 李杨. 基于事件触发的多智能体系统差分隐私保护跟踪控制[J]. 广东工业大学学报, 2025, 42(2): 70–80. DOI： 10.12052/gdutxb.240022

Xie Guangqiang, Hu Mingyu, Li Yang. Event-triggered Differential Privacy Protection Tracking Control[J]. 2025, 42(2): 70-80. DOI： 10.12052/gdutxb.240022.

摘要

为了应对传统跟踪控制方法可能引起的窃听者攻击风险，多智能体系统跟踪控制研究需要考虑隐私保护问题。本文在同时存在领导者与跟随者的多智能体系统中，针对跟踪控制隐私保护问题，提出了基于事件触发的分布式差分隐私保护跟踪控制方法(Event-triggered Distributed Differential Privacy Protection Tracking Control

EDPTC)。该方法旨在时刻保障领导者与跟随者的状态隐私，同时实现均方跟踪。考虑到领导者与跟随者状态更新的差异，基于敏感度上界定理，分别设计了适应各自特点的隐私保护机制：跟随者的递减噪声机制(The Decreasing Noise Mechanism of Followers

DNMF) 和领导者的随机噪声机制(The Random Noise Mechanism of Leaders

RNML)。此外，为减少随机噪声对控制效果的影响，引入领导者状态估计算法，并设计分布式事件触发器以降低通信频率。通过矩阵分析和概率论，证明了EDPTC的隐私性并推导出了其实现均方跟踪的充分条件。最后，通过一系列数值仿真验证了方法的有效性。

Abstract

To counter the risk of eavesdropper attacks inherent in traditional tracking control methods

research on tracking control in multi-agent systems must incorporate privacy protection considerations. This study introduces an event-triggered distributed differential privacy protection tracking control (EDPTC) method in multi-agent systems featuring both leaders and followers

aimed at addressing privacy protection issues in tracking control. The method is designed to ensure the privacy of the states of leaders and followers at all times while achieving mean square tracking. Given the differences in state updates between leaders and followers

privacy protection mechanisms tailored to each party are developed based on the sensitivity upper bound theorem: the decreasing noise mechanism for followers (DNMF) and the random noise mechanism for leaders (RNML) . Moreover

to minimize the impact of random noise on control performance

a leader state estimation algorithm is introduced

and a distributed event trigger is designed to reduce the communication frequency. Additionally

through matrix analysis and probability theory

the privacy of the EDPTC is proven

and sufficient conditions for achieving mean square tracking are derived. Finally

a series of numerical simulations validate the effectiveness of the proposed method.

关键词

Keywords

references

AMIRKHANI A, BARSHOOI AH. Consensus in multi-agent systems: a review [J]. Artificial Intelligence Review, 2022, 55(5): 3897-3935.

WANG S, WAN J, ZHANG D, et al . Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination [J ] . Computer Networks, 2016, 101: 158-168.

XIE G, XU H, LI Y, et al . Fast distributed consensus seeking in large-scale and high-density multi-agent systems with connectivity maintenance [J ] . Information Sciences, 2022, 608: 1010-1028.

MAZZARINO P R, MACII A, BOTTACCIOLI L, et al . A multi-agent framework for smart grid simulations: strategies for power-to-heat flexibility management in residential context [J ] . Sustainable Energy, Grids and Networks, 2023, 34: 101072.

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

AZARBAHRAM A, AMINI A, PARIZ N. Event-triggered tracking formation of networked nonlinear intelligent transportation systems surrounded by random disturbances [J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(11): 21959-21970.

BALBO F, MANDIAU R, ZARGAYOUNA M. Extended review of multi-agent solutions to advanced public transportation systems challenges[J]. Public Transport, 2024, 16: 1-28.

XIE G Q, ZHAO J W, LI Y, et al . Cooperative lane-changing based on multi-cluster system [J ] . Journal of Guangdong University of Technology, 2021, 38(5): 1-9.

ZHANG D, FENG G, SHI Y, et al . Physical safety and cyber security analysis of multi-agent systems: a survey of recent advances [J ] . IEEE/CAA Journal of Automatica Sinica, 2021, 8(2): 319-333.

GONG Y, XUE H, PAN Y, et al . Distributed event-triggered tracking consensus control for privacy preservation in multi-agent systems with denial-of-service attacks [J ] . International Journal of Adaptive Control and Signal Processing, 2022, 36(8): 1860-1878.

DWORK C. Differential privacy[C]//Automata, Languages and Programming: 33rd International Colloquium.Venice: Springer Berlin Heidelberg, 2006: 1-12.

HUANG Z, MITRA S, DULLERUD G. Differentially private iterative synchronous consensus[C]// In Proceedings of the 2012 ACM Workshop on Privacy in the Electronic Society (WPES '12). New York: ACM, 2012: 81-90.

NOZARI E, TALLAPRAGADA P, CORTÉS J. Differentially private average consensus: obstructions, trade-offs, and optimal algorithm design [J]. Automatica, 2017, 81: 221-231.

GAO L, DENG S, REN W. Differentially private consensus with an event-triggered mechanism [J]. IEEE Transactions on Control of Network Systems, 2018, 6(1): 60-71.

ZHA J, HAN L, DONG X, et al . Privacy-preserving push-sum distributed cubature information filter for nonlinear target tracking with switching directed topologies [J ] . ISA Transactions, 2023, 136: 16-30.

GUSRIALDI A. Resilient and privacy-preserving leader-follower consensus in presence of cyber-attacks [J]. IEEE Control Systems Letters, 2023, 7: 3211-3216.

XIE G, CHEN J, LI Y. Hybrid-order network consensus for distributed multi-agent systems [J]. Journal of Artificial Intelligence Research, 2021, 70: 389-407.

ZHANG P, LIU T, CHEN J, et al . Recent developments in event-triggered control of nonlinear systems: anoverview [J ] . Unmanned Systems, 2023, 11(1): 27-56.

XIA L, LI Q, SONG R. Adaptive event-triggered average tracking control with activable event-triggering mechanisms [J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(10): 6067-6079.

HUANG Y, LIU Y. Practical tracking via adaptive event-triggered feedback for uncertain nonlinear systems [J]. IEEE Transactions on Automatic Control, 2019, 64(9): 3920-3927.

CORTS J, DULLERUD G E, HAN S, et al. Differential privacy in control and network systems[C ] // 2016 IEEE 55th Conference on Decision and Control (CDC) , Las Vegas: IEEE, 2016: 4252-4272.

WANG Y, LAM J, LIN H. Consensus of linear multivariable discrete-time multiagent systems: differential privacy perspective [J]. IEEE Transactions on Cybernetics, 2022, 52(12): 13915-13926.

REN W, BEARD R W. Consensus seeking in multiagent systems under dynamically changing interaction topologies [J]. IEEE Transactions on Automatic Control, 2005, 50(5): 655-661.

HU J, HONG Y. Leader-following coordination of multi-agent systems with coupling time delays [J]. Physica A: Statistical Mechanics and its Applications, 2007, 374(2): 853-863.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Consensus of Switched Topology in Multi-agent System Based on Layered Neighbor Selection

Event-Triggered Mechanism Based Non-Fragile Consensus Control for Multi-Rate Multi-Agent Systems

A Data-Driven Prescribed Convergence Rate Design for Robust Tracking of Discrete-Time Systems

Cooperative Lane-changing Based on Multi-cluster System

A Research on the Consensus Problem of Multi-agent Systems with Random Time Delays Based on Model Reduction

Related Author

Xie Guang-qiang

Wan Zi-kun

Liu Jian-hua

Li Jia-hui

Liu Xiao-bin

Mu Shu-juan

Dong Hong-li

Chen Ci

Related Institution

东北石油大学人工智能能源研究院

东北石油大学黑龙江省网络化与智能控制重点实验室

东北石油大学三亚海洋油气研究院

上海电子信息职业技术学院中德工程学院

School of Automation, Guangdong University of Technology

AI问答

⁰