Abstract: How to improve uniform convergence rate of multi-agent systems is an important issue in uniform research.The uniform convergence rate can be well performed by the smallest non-zero eigenvalues of the Laplacian matrix.According to the computer simulation,this paper found that the uniform convergence rate is significantly led by different factors in different complex networks.The methods for impraing uniform convergence rate on the different complex networks are listed as follows.For the nearest-neighbor coupled network,the number of nodes N should be reduced,or the number of coupling K should be increased.For the NW small-world network,the number of nodes N should be increased,or the probability of random edged p should be increased.This paper found that the convergence rate has a good linear relationship between the number of nodes N and the probability of random edges p.For the Waxman random graph network,the number of the nodes N should be increased,or the network parameters α and β should be increased.The convergence rate is linear when β increases,but there is a slight fluctuation.The results can help to optimize the convergence rate of multi-agent network.

Key words: Complex network, Consensus, Multi-agent systems, Nearest-neighbor coupled network, NW small-world network, Random graph network