Fully Distributed Model-Free Flocking of Multiple Euler-Lagrange Systems

Abstract

In this paper, we investigate the leader-follower flocking issue of multiple Euler-Lagrange systems (MELSs) with time-varying input disturbances and completely unknown model parameter information under a proximity graph. Particularly, each follower can only access information from other agents that the relative distance between them is not greater than communication distance. Firstly, based on adaptive control theory, we propose a model-free leader-follower flocking algorithm with constant coupling gains, that is the controller design does not require any dynamic parameter information. Then, for fully distributed design (i.e. no requirement for any global information of the communication graph), edge-based adaptive coupling gains are applied for the above algorithm. The leader-follower flocking of MELSs can be achieved by all proposed algorithms under a connected and no-collision initial proximity graph. Finally, we show some simulation results to illustrate the effectiveness of all proposed flocking algorithms.