Fast consensus of high-order multi-agent systems
Jiahao Dai, Jing-Wen Yi, Li Chai

TL;DR
This paper develops an accelerated consensus algorithm for high-order multi-agent systems, linking convergence rate to control gains, and introduces a finite-time consensus protocol with explicit gain formulas, validated through simulations.
Contribution
It proposes a gradient descent-based accelerated consensus algorithm with explicit control gain formulas and a finite-time consensus protocol for high-order multi-agent systems.
Findings
Established the link between convergence rate and control gains.
Derived explicit formulas for control gains and final consensus state.
Validated the theoretical results with numerical examples and simulations.
Abstract
In this paper, the fast consensus problem of high-order multi-agent systems under undirected topologies is considered. The direct link between the consensus convergence rate and the control gains is established. An accelerated consensus algorithm based on gradient descent is proposed to optimize the convergence rate. By applying the Routh-Hurwitz stability criterion, the lower bound on the convergence rate is derived, and explicit control gains are derived as the necessary condition to achieve the optimal convergence rate. Moreover, a protocol with time-varying control gains is designed to achieve the finite-time consensus. Explicit formulas for the time-varying control gains and the final consensus state are given. Numerical examples and simulation results are presented to illustrate the obtained theoretical results.
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Taxonomy
TopicsDistributed Control Multi-Agent Systems · Neural Networks Stability and Synchronization · Mathematical and Theoretical Epidemiology and Ecology Models
