Investigating Nonlinear Consensus Interaction in Multi-Agent Systems: Exploring Symmetry and Asymmetry

This research introduces exponential quadratic stochastic consensus (EQSC), a novel approach to achieving consensus in multi-agent systems (MAS) under undirected graph topology. EQSC combines symmetric and asymmetric nonlinear interactions, leveraging quadratic random factors and matrix theories. The proposed method controls nonlinear redundancy within MAS, aiming for convergence through simplified calculations compared to linear and nonlinear consensus models. Our findings demonstrate that EQSC achieves consensus more rapidly than other models and is effective in communication scenarios where alternative models may fail. Theoretical analysis and simulations validate the effectiveness of EQSC in fostering consensus within MAS.