Fully distributed consensus control for stochastic multi-agent systems under undirected and directed topologies
This work addresses a critical gap in distributed control for stochastic multi-agent systems, offering practical protocols for applications like robotics or sensor networks, though it appears incremental in extending existing consensus methods to stochastic settings.
The paper tackled the design of fully distributed control protocols for stochastic consensus in multi-agent systems, establishing the existence and uniqueness of solutions for path-dependent nonlinear systems under undirected and directed topologies, and provided explicit exponential convergence rate estimates validated by simulations.
This work aims to address the design of fully distributed control protocols for stochastic consensus, and, for the first time, establishes the existence and uniqueness of solutions for the path-dependent and highly nonlinear closed-loop systems under both undirected and directed topologies, bridging a critical gap in the literature. For the case of directed graphs, a unified fully distributed control protocol is designed for the first time to guarantee mean square and almost sure consensus of stochastic multi-agent systems under directed graphs. Moreover, an enhanced fully distributed protocol with additional tunable parameters designed for undirected graphs is proposed, which guarantees stochastic consensus while achieving superior convergence speed. Additionally, our work provides explicit exponential estimates for the corresponding convergence rates of stochastic consensus, elucidating the relationship between the exponential convergence rate and the system parameters. Simulations validate the theoretical results.