Distributed Dynamic Weighted Average Consensus for Disturbed Multiagent Systems in Fixed Time

Abstract

This article addresses the dynamic weighted average consensus (DWAC) problem of disturbed first-order multiagent systems, where a group of agents work cooperatively to track the weighted average of multiple time-varying signals. A class of distributed continuous-time algorithms are proposed to achieve DWAC within a fixed settling time, regardless of the initial conditions of the agents' states. Our first algorithm achieves accurate tracking of the desired trajectory by taking advantage of the variable structure property of sign functions. The second algorithm achieves uniformly bounded tracking with adjustable tracking error bounds by applying the continuous control law. Lyapunov method based stability analysis shows that both the algorithms achieve the fixed-time tracking control even when the single-integrator agent dynamics are affected by bounded disturbances. Moreover, the relationships between controller parameters and tracking performance are derived and the upper bounds of settling time are estimated. Finally, the proposed algorithms are applied to solve the distributed time-varying quadratic optimization problem, and the simulation results confirm the effectiveness of the proposed distributed fixed-time DWAC algorithms.