Distributed finite-time coordinated tracking control for multiple Euler–Lagrange systems with input nonlinearity

Abstract

In this paper, distributed finite-time coordinated tracking control for multiple Euler–Lagrange systems with input nonlinearity is investigated by using backstepping design technique under directed topology. The controller is designed under the condition that the information of the dynamic leader is available to only a subset of the followers. We first design an auxiliary variable relating to trajectory errors among neighbor agents. Then a distributed finite-time tracking control algorithm is developed where two neural networks are used to approximate the nonlinear model uncertainties and input nonlinearity, respectively. When considering that there exists incomplete known state for each follower, a modified distributed finite-time tracking control strategy is designed by utilizing high-gain observers. Based on backstepping method, finite-time technique, and graph theory, both proposed control strategies guarantee that tracking errors between each follower and the leader could be ultimately bounded in finite time. Numerical simulations show the superiorities of the proposed protocols by comparisons with existing methods.