TY - JOUR
T1 - Differentially Private Consensus Control for Discrete-time Multi-Agent Systems
T2 - Encoding-Decoding Schemes
AU - Gao, Chen
AU - Wang, Zidong
AU - He, Xiao
AU - Liu, Yang
AU - Yue, Dong
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 61933007 and Grant 62233012, in part by the National Key Research and Development Program of China under Grant 2022YFB25031103, in part by the Huaneng Group Science and Technology Research Project of China under Grant HNKJ22-H105, in part by the Royal Society of the U.K., and in part by the Alexander Von Humboldt Foundation of Germany.
Publisher Copyright:
© 1963-2012 IEEE.
PY - 2024/8/1
Y1 - 2024/8/1
N2 - This article is concerned with the differentially private consensus control (DPCC) problem for linear discrete-time multiagent systems (MASs) under dynamic encoding-decoding schemes (EDSs), where the agents' initial states are the sensitive data to be protected from potential eavesdroppers. The EDS is deployed on each agent to compress the data before transmission so as to better utilize the limited network bandwidth. Differential privacy, as a performance metric, is introduced to evaluate the level of privacy, and an EDS-based DPCC scheme is proposed to ensure the ultimate mean-square consensus with preserved differential privacy. A set of criteria is first established for the EDS-embedded DPCC problem in terms of the performance of consensus, the size of transmitted data, and the level of privacy. Subsequently, the codesign issue is discussed for the EDS, the differentially private mechanism, and the consensus controller. Finally, the effectiveness of the developed algorithm is illustrated via numerical simulations.
AB - This article is concerned with the differentially private consensus control (DPCC) problem for linear discrete-time multiagent systems (MASs) under dynamic encoding-decoding schemes (EDSs), where the agents' initial states are the sensitive data to be protected from potential eavesdroppers. The EDS is deployed on each agent to compress the data before transmission so as to better utilize the limited network bandwidth. Differential privacy, as a performance metric, is introduced to evaluate the level of privacy, and an EDS-based DPCC scheme is proposed to ensure the ultimate mean-square consensus with preserved differential privacy. A set of criteria is first established for the EDS-embedded DPCC problem in terms of the performance of consensus, the size of transmitted data, and the level of privacy. Subsequently, the codesign issue is discussed for the EDS, the differentially private mechanism, and the consensus controller. Finally, the effectiveness of the developed algorithm is illustrated via numerical simulations.
KW - Consensus control
KW - Decoding
KW - differential privacy
KW - Differential privacy
KW - Electronic mail
KW - encoding-decoding scheme
KW - Laplace equations
KW - mean-square consensus
KW - multi-agent system
KW - Privacy
KW - Vectors
KW - encoding-decoding scheme (EDS)
KW - multiagent system (MAS)
UR - http://www.scopus.com/inward/record.url?scp=85186069661&partnerID=8YFLogxK
U2 - 10.1109/TAC.2024.3367803
DO - 10.1109/TAC.2024.3367803
M3 - Article
AN - SCOPUS:85186069661
VL - 69
SP - 5554
EP - 5561
JO - IEEE Transactions on Automatic Control
JF - IEEE Transactions on Automatic Control
SN - 0018-9286
IS - 8
M1 - 10440469
ER -