Prescribed-Time Sampled-Data Control for the Bipartite Consensus of Linear Multi-Agent Systems in Singed Networks.

This article examines the prescribed-time sampled-data control problem for multi-agent systems in signed networks. A time-varying high gain-based protocol is devised to solve the prescribed-time bipartite consensus problem of the linear multi-agent systems with the control gain matrix being resolved through the utilization of the parametric Lyapunov equation. By using the method of scalarization, sufficient conditions are attained to ensure the prescribed-time bipartite consensus of linear multi-agent systems, where the maximum allowable sampling interval (MASI) ensuring the prescribed-time consensus is determined by the initial values of the system state, the linear dynamics of the system, and the maximum eigenvalue of the Laplacian matrix. Specifically, the MASI is inversely proportional to the maximum eigenvalue of the Laplacian matrix. Finally, the validity of the conclusion is ensured through numerical simulation. [ABSTRACT FROM AUTHOR]