Constrained Consensus in State-Dependent Directed Multiagent Networks

Abstract

In this paper, constrained consensus of a group of continuous-time dynamical agents over state-dependent networks is investigated. The communication network, modulated by an asymmetric distance between agents, accommodates general directed information flows. Each agent proposes a comfortable range in a distributed manner, where they are inclined to agree on the final equilibrium state. Based on Lyapunov stability theory and robustness analysis, different conditions have been obtained to guarantee convergence within the common comfortable range when the network connectivity is fixed and time-varying. No global information is required in the proposed nonlinear control protocols. Furthermore, an opinion dynamics model has been introduced incorporating both social observer effect and bounded confidence phenomenon in the same state-dependent framework. Relaxed consensus conditions have been derived under certain symmetric assumptions. Finally, numerical examples have been presented to verify the effectiveness of the theoretical results.

Analysis of the consensus of double-layer chain networks

“…The study of complex networks has not only profound theoretical significance but also has a wide range of practical applications. With the deepening of research, scholars have made new progress in synchronization and propagation of complex networks [3,4], consensus and robustness [5][6][7][8][9][10][11], fractal networks [12,13], cascading failures [14].…”

Clusters in multi-leader directed consensus networks

“…Multi-agent systems have attracted a significant amount of research interest due to their theoretical challenges and richness of applications [1]- [3]. In particular, directed networks have received considerable attention [4], [5]. In directed networks, agents often tend to aggregate into clusters depending on factors such as the values of the network's edge weights, node dynamics, and the topology of network.…”