Nonlinear Fixed-Time Bipartite Consensus Algorithm for Multiagent Systems

In the paper, we consider the uncertain nonlinear multi-agent systems over antagonistic networks and design an algorithm to achieve bipartite consensus in a fixed time. The algorithm drives each agent of multi-agent systems to achieve bipartite consensus, and the achieved bipartite consensus has the same modules but opposite signs when the antagonistic network is structurally balanced. Compared with the traditional asymptotic consensus and the finite-time consensus, the fixed-time bipartite consensus can reach convergence faster, and the settling time is independent of the initial states of the system. Finally, the simulation results verify the validity of the proposed theoretical results.