| 引用本文: | 孙玉娇,杨洪勇,于美妍.具有切换拓扑的多智能体系统协同控制的差分隐私保护[J].控制理论与应用,2022,39(7):1345~1352.[点击复制] |
| SUN Yu-jiao,YANG Hong-yong,YU Mei-yan.Differential privacy protection for cooperative control of multi-agent systems with switching topologies[J].Control Theory and Technology,2022,39(7):1345~1352.[点击复制] |
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| 具有切换拓扑的多智能体系统协同控制的差分隐私保护 |
| Differential privacy protection for cooperative control of multi-agent systems with switching topologies |
| 摘要点击 1234 全文点击 433 投稿时间：2021-09-13 修订日期：2022-03-28 |
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| DOI编号 10.7641/CTA.2021.10861 |
| 2022,39(7):1345-1352 |
| 中文关键词 多智能体 敏感信息 差分隐私 切换拓扑 |
| 英文关键词 multi-agent systems sensitive information differential privacy switching topologies |
| 基金项目 国家自然科学基金项目(61673200)资助. |
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| 中文摘要 |
| 网络信息技术的不断发展与普及使得各类数据的发布采集变得方便与便捷, 但数据的直接发布势必会造
成个网络信息的泄露和敏感信息的失密, 因此敏感信息的保护成为了各行各业关注的问题. 本文研究了基于固定拓
扑和切换拓扑的多智能体系统协同控制的差分隐私保护问题, 将差分隐私算法与传统平均一致性算法结合, 提出了
具有隐私保护的协同控制算法, 分析了隐私保护算法对分布式协同控制闭环系统稳定性的影响. 基于所提算法, 应
用矩阵论和概率统计对隐私保护协同控制算法的收敛性和隐私性进行理论分析, 该算法可以保护智能个体的数据
隐私, 同时可以使得系统运动实现均方一致. 在系统拓扑结构动态变化的情况下, 本文对该算法的收敛性和隐私性
进行理论分析, 讨论了切换拓扑对隐私保护的影响. 最后的仿真示例验证了理论结果的正确性. |
| 英文摘要 |
| With the continuous development and popularization of network information technology, the release and
collection of all kinds of data become more and more convenient. However, the direct release of data will inevitably lead
to the leakage of network information and the loss of sensitive information, so the protection of sensitive information
has become a concern of all walks of life. In this paper, the differential privacy problem of cooperative control for firstorder
multi-agent systems based on fixed topology and switched topology is studied. A cooperative control algorithm
with privacy is proposed by combining the differential privacy algorithm and the average consistency algorithm, and the
influence of privacy protection algorithm on the stability of distributed cooperative control closed-loop system is analyzed.
Based on the proposed algorithm, the convergence and the privacy of privacy protection cooperative control algorithm
are theoretically analyzed by using matrix theory and probability statistics. The algorithm can protect the data privacy
of intelligent individuals and make the system motion achieve mean square consistency. In the case of dynamic system
topologies, the convergence and privacy of the algorithm is analyzed, and the impact of switching topologies on privacy
protection is discussed. Finally, numerical simulations are shown to verify the correctness of the results. |
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