控制理论与应用2026，Vol.43Issue(5)：1011-1022,12.DOI:10.7641/CTA.2025.40646
具有隐私保护的多智能体系统自适应分布式优化控制
Adaptive distributed optimization control for privacy-preserving multi-agent systems
摘要
Abstract
This paper investigates the distributed optimization problem for multi-agent systems(MASs)with privacy preservation.In practice,MASs often face the risk of privacy leakage.To address this,this paper proposes a state encryption function to protect the information exchanged between communicating agents and prevent potential data leakage.Adaptive control parameters are designed to dynamically adjust communication weights based on the state differences between agents,thereby accelerating the system's convergence rate.Assuming that the global objective function of the system is the sum of the local objective functions of all agents,the paper develops a gradient tracking method to estimate the average gradient sum.A distributed optimization control algorithm is proposed,enabling agents to achieve global optimization using local information without relying on global data.Through performance analysis,the proposed method is shown to effectively protect the data privacy of the MASs while ensuring that the motion trajectories of the agents rapidly converge to the optimal solution of the objective function.Finally,the effectiveness of the privacy-preserving method and the distributed control protocol is validated through simulation experiments.关键词
多智能体系统/分布式优化/隐私保护/自适应控制/梯度跟踪Key words
multi-agent systems/distributed optimizatio/privacy preservation/adaptive control/gradient tracking引用本文复制引用
李芮,杨洪勇,潘龙硕..具有隐私保护的多智能体系统自适应分布式优化控制[J].控制理论与应用,2026,43(5):1011-1022,12.基金项目
国家自然科学基金项目(61673200),山东省自然科学基金项目(ZR2022MF231),鲁东大学研究生创新项目(IPGS2025-073)资助.Supported by the National Natural Science Foundation of China(61673200),the National Natural Science Foundation of Shandong Province(ZR2022MF231)and the Graduate Innovation Project of Ludong University(IPGS2025-073). （61673200）
