Fixed-time consensus protocols for multi-agent systems with linear and nonlinear state measurements

This paper deals with fixed-time consensus problem for multi-agent systems under detail-balanced directed graph, where both protocols with linear and nonlinear state measurements are proposed. For the case where linear state measurements are available, protocols are presented with uniformly bounded setting time for any initial condition. By introducing a class of admissible nonlinear functions, consensus protocols with linear measurements are extended to protocols with nonlinear measurements. It also can be proven that under nonlinear measurement protocols, the states of the agents can also converge to a common value with a uniformly bounded setting time. Numerical simulations are presented to demonstrate the efficiency of our proposed protocols.