Adaptive Prescribed-Time Consensus for a Class of Nonlinear Multi-Agent Networks by Bounded Time-Varying Protocols
Zain ul Aabidin Lodhi, Kai Zhang, Bin Zhou, Huaiyuan Jiang
Abstract
This paper delves into the adaptive prescribed-time leader-following consensus control within a class of nonlinear networked multi-agent systems. Firstly, the nonlinear multi-agent network subjected to matched disturbances employs parameterization of the non-identical unknown nonlinear dynamics. Distributed bounded protocols leveraging parametric Lyapunov equation and adaptive laws are introduced, incorporating local consensus errors and relative state feedback. The proposed solution attains prescribed-time consensus, ensuring the boundedness of estimated parameters. Subsequently, building upon these findings, fully distributed adaptive bounded protocols for the nonlinear multi-agent networks in the lower triangular structure are presented. These fully distributed protocols rely solely on the relative states between the neighboring agents and do not necessitate information about the underlying communication topology to attain a prescribed-time consensus. Finally, the established results are substantiated through numerical examples, illustrating their effectiveness.