Paper
12 December 2021 Comparison of consensus in different multi-agent networks with diverse time-delays
Yingfan Gao
Author Affiliations +
Proceedings Volume 12127, International Conference on Intelligent Equipment and Special Robots (ICIESR 2021); 121272O (2021) https://doi.org/10.1117/12.2625556
Event: International Conference on Intelligent Equipment and Special Robots (ICIESR 2021), 2021, Qingdao, China
Abstract
This paper presents the consensus control with diverse time-delays on multi-agent systems. Depending on the comparison among the performances (the speed of convergence, robustness, and synchronization) of different graphs on the consensus problem without the mathematical analysis of algebraic connectivity, the current study aims to emphasize the importance of the structure of networks, comprising nodes and edges, in control engineering. This research is based on three typical complex networks (Balanced digraph, Regular Lattice-Type Nearest-Neighbor Graph, and Small-World Network) whose initial state, number of nodes (NV = 10), and edges (NE = 20) are consistent. The most significant difference among networks is the degree of graphs. The simulation results of the consensus control with different time-delays on these graphs with single integrator dynamics agents are collected to find the relationship between the degree of network and time-delays. The communication time delays are chosen from τ = [0,0.1,0.2,0.23,0.3,0.4]. Finally, it is found that graphs with bigger degree have better robustness to time-delays. And there is a general trade-off between convergence speed and robustness to time-delay, though slight time-delay may benefit the consensus. What’s more, it is proved in this study that the degree of graphs is not sufficient to determine the accurate maximum of time-delays.
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Yingfan Gao "Comparison of consensus in different multi-agent networks with diverse time-delays", Proc. SPIE 12127, International Conference on Intelligent Equipment and Special Robots (ICIESR 2021), 121272O (12 December 2021); https://doi.org/10.1117/12.2625556
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KEYWORDS
Control systems

Analytical research

Mathematics

Unmanned aerial vehicles

Robotics

Systems modeling

Modeling and simulation

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