Privacy-Preserving Dynamic Average Consensus via State Decomposition: Case Study on Multi-Robot Formation Control

Privacy-Preserving Dynamic Average Consensus via State Decomposition: Case Study on Multi-Robot Formation Control
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DOI:
10.1016/j.automatica.2022.110182
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发表时间:
2020-08
期刊:
ArXiv
影响因子:
--
通讯作者:
Kaixiang Zhang;Zhaojian Li;Yongqiang Wang;Ali Louati;Jian Chen
Kaixiang Zhang;Zhaojian Li;Yongqiang Wang;Ali Louati;Jian Chen
中科院分区:
其他
文献类型:
--
作者:
Kaixiang Zhang;Zhaojian Li;Yongqiang Wang;Ali Louati;Jian Chen

文献摘要

相似文献

动态平均共识是一个分散的控制/估计框架,其中一组代理合作跟踪本地时变参考信号的平均值。在本文中,我们开发了一种新的基于状态分解的隐私保护方案,以保护隐私的代理共享信息时,与邻近的代理。具体来说,我们首先表明,一个外部窃听者可以成功窃听的参考信号的所有代理在传统的动态平均共识算法。为了保护隐私免受窃听者的攻击,开发了一种状态分解方案,其中每个代理的原始状态被分解为两个子状态:一个继承原始状态在节点间交互中的作用,而另一个子状态只与第一个通信,并且对其他相邻代理不可见。严格的分析表明:(1)所提出的隐私方案保持了平均共识的收敛性;(2)保护了代理的隐私,使得窃听者无法以保证的准确性发现私人参考信号。将所提出的隐私保护动态平均一致性框架应用于多个非完整移动的机器人的编队控制中,验证了该方案的有效性.数值仿真结果验证了该方法的有效性。
Dynamic average consensus is a decentralized control/estimation framework where a group of agents cooperatively track the average of local time-varying reference signals. In this paper, we develop a novel state decomposition-based privacy preservation scheme to protect the privacy of agents when sharing information with neighboring agents. Specifically, we first show that an external eavesdropper can successfully wiretap the reference signals of all agents in a conventional dynamic average consensus algorithm. To protect privacy against the eavesdropper, a state decomposition scheme is developed where the original state of each agent is decomposed into two sub-states: one succeeds the role of the original state in inter-node interactions, while the other sub-state only communicates with the first one and is invisible to other neighboring agents. Rigorous analyses are performed to show that (1) the proposed privacy scheme preserves the convergence of the average consensus; and (2) the privacy of the agents is protected such that an eavesdropper cannot discover the private reference signals with guaranteed accuracy. The developed privacy-preserving dynamic average consensus framework is then applied to the formation control of multiple non-holonomic mobile robots, in which the efficacy of the scheme is demonstrated. Numerical simulation is provided to illustrate the effectiveness of the proposed approach.