TY - JOUR
T1 - A Distributed Consensus Protocol Based on Neighbor Selection Strategies for Multi-Agent Systems Convergence
AU - Xie, Guangqiang
AU - Lan, Tianxiang
AU - Hu, Xianbiao
AU - Li, Yang
AU - Wang, Chang Dong
AU - Yin, Yuyu
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2019
Y1 - 2019
N2 - Multi-agent systems (MASs), which consist of numerous mobile agents, is a promising research area in artificial intelligence that has been profusely applied to Engineering. A consensus problem of discrete time MASs with switching topology is investigated in this paper. First, a new distributed consensus protocol based on different neighbor selection strategies is proposed. In order to reach system consensus, the protocol requires each agent to intelligently refer to two neighbors for calculating and updating state. Compared with traditional protocol, the new protocol with different strategies can significantly reduce the cost of comparison, data storage and computation during MASs evolution. Next, three concrete neighbor selection strategies and an optimized strategy are designed. Then, we analyze and prove the stability of the protocol by Lyapunov theorem and Gerschgorin Theorem. The range of parameters, that affect reaching a consensus and equilibrium state in each strategy, is given in the proof. Finally, the experimental results demonstrate the effectiveness of the new protocol and the convergence performance of MASs under different neighbor selection strategies and parameter settings.
AB - Multi-agent systems (MASs), which consist of numerous mobile agents, is a promising research area in artificial intelligence that has been profusely applied to Engineering. A consensus problem of discrete time MASs with switching topology is investigated in this paper. First, a new distributed consensus protocol based on different neighbor selection strategies is proposed. In order to reach system consensus, the protocol requires each agent to intelligently refer to two neighbors for calculating and updating state. Compared with traditional protocol, the new protocol with different strategies can significantly reduce the cost of comparison, data storage and computation during MASs evolution. Next, three concrete neighbor selection strategies and an optimized strategy are designed. Then, we analyze and prove the stability of the protocol by Lyapunov theorem and Gerschgorin Theorem. The range of parameters, that affect reaching a consensus and equilibrium state in each strategy, is given in the proof. Finally, the experimental results demonstrate the effectiveness of the new protocol and the convergence performance of MASs under different neighbor selection strategies and parameter settings.
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U2 - 10.1109/ACCESS.2019.2939207
DO - 10.1109/ACCESS.2019.2939207
M3 - Article
AN - SCOPUS:85077967160
SN - 2169-3536
VL - 7
SP - 132937
EP - 132949
JO - IEEE Access
JF - IEEE Access
M1 - 8825994
ER -