There has been significant recent research on secure control problems that arise from the open and complex realworld industrial environments.This paper focuses on addressing the issue of secure consensus control in mu...There has been significant recent research on secure control problems that arise from the open and complex realworld industrial environments.This paper focuses on addressing the issue of secure consensus control in multi-agent systems(MASs)under malicious attacks,utilizing the practical Byzantine fault tolerance(PBFT)and Raft consensus algorithm in blockchain.Unlike existing secure consensus control algorithms that have strict requirements for topology and high communication costs,our approach introduces a node grouping methodology based on system topology.Additionally,we utilize the PBFT consensus algorithm for intergroup leader identity verification,effectively reducing the communication complexity of PBFT in large-scale networks.Furthermore,we enhance the Raft algorithm through cryptographic validation during followers’log replication,which enhances the security of the system.Our proposed consensus process not only identifies the identities of malicious agents but also ensures consensus among normal agents.Through extensive simulations,we demonstrate robust convergence,particularly in scenarios with the relaxed topological requirements.Comparative experiments also validate the algorithm’s lower consensus latency and improved efficiency compared to direct PBFT utilization for identity verification and classical secure consensus control method mean subsequence reduced(MSR)algorithm.展开更多
The problem of secure consensus for multi-agent systems(MASs)is tackled in this study.The self-triggering strategy is designed to enable each healthy agent to estimate its next triggering step at the current triggerin...The problem of secure consensus for multi-agent systems(MASs)is tackled in this study.The self-triggering strategy is designed to enable each healthy agent to estimate its next triggering step at the current triggering step.Thus,each healthy agent only needs to sense and broadcast at its triggering steps,and to monitor the latest broadcast states of their neighbors at their triggering steps.The frequent monitoring is thereby mitigated.Subsequently,a self-triggering secure consensus algorithm is developed to guarantee that the state variables of healthy agents reach consensus despite the influence of faulty agents in the network.The convergence analysis of the proposed method is conducted with graph tools and Lyapunov theory.Numerical examples are given to illustrate the superior performance of the proposed self-triggering secure consensus algorithm compared with the existing methods based on the static and dynamic event-triggering mechanisms.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(NS2024021)the Science and Technology Development Fund of Macao SAR(0145/2023/RIA3,0093/2023/RIA2,0050/2020/A1)the National Natural Science Foundation of China(62103411).
文摘There has been significant recent research on secure control problems that arise from the open and complex realworld industrial environments.This paper focuses on addressing the issue of secure consensus control in multi-agent systems(MASs)under malicious attacks,utilizing the practical Byzantine fault tolerance(PBFT)and Raft consensus algorithm in blockchain.Unlike existing secure consensus control algorithms that have strict requirements for topology and high communication costs,our approach introduces a node grouping methodology based on system topology.Additionally,we utilize the PBFT consensus algorithm for intergroup leader identity verification,effectively reducing the communication complexity of PBFT in large-scale networks.Furthermore,we enhance the Raft algorithm through cryptographic validation during followers’log replication,which enhances the security of the system.Our proposed consensus process not only identifies the identities of malicious agents but also ensures consensus among normal agents.Through extensive simulations,we demonstrate robust convergence,particularly in scenarios with the relaxed topological requirements.Comparative experiments also validate the algorithm’s lower consensus latency and improved efficiency compared to direct PBFT utilization for identity verification and classical secure consensus control method mean subsequence reduced(MSR)algorithm.
基金supported by the National Natural Science Foundation of China(Grant Nos.62173147,62303030,62403028 and U2233212)Beijing Municipal Natural Science Foundation(Grant No.L221008)+1 种基金Open Fund of Science and Technology on Thermal Energy and Power Laboratory(Grant No.TPL2022C02)Postdoctoral Fellowship Program of CPSF(Grant No.GZC20233377)
文摘The problem of secure consensus for multi-agent systems(MASs)is tackled in this study.The self-triggering strategy is designed to enable each healthy agent to estimate its next triggering step at the current triggering step.Thus,each healthy agent only needs to sense and broadcast at its triggering steps,and to monitor the latest broadcast states of their neighbors at their triggering steps.The frequent monitoring is thereby mitigated.Subsequently,a self-triggering secure consensus algorithm is developed to guarantee that the state variables of healthy agents reach consensus despite the influence of faulty agents in the network.The convergence analysis of the proposed method is conducted with graph tools and Lyapunov theory.Numerical examples are given to illustrate the superior performance of the proposed self-triggering secure consensus algorithm compared with the existing methods based on the static and dynamic event-triggering mechanisms.
