Distributed adaptive containment control for networked uncertain Euler–Lagrange systems

Abstract

The paper is concerned with the containment problem of a multi-agent system with each agent being described by an Euler–Lagrange (EL) equation with uncertain parameters. Distributed adaptive control laws are proposed such that the generalised positions of the EL systems converge to the target convex set without measuring or observing neighbours' velocities. Moreover, exponential rate convergence is obtained when the regressor matrix of each EL system is of full column rank. As a byproduct, some of the uncertain parameters existing in the EL systems can be identified under the full column rank condition. Finally, the effectiveness of the proposed method is validated through the simulations on a group of networked uncertain robots.