Model-Independent Containment Control for Dynamic Multiple Euler-Lagrange Systems With Disturbances and Uncertainties
Housheng Su, Liren Zhang
Abstract
This article studies the model-independent distributed containment control problem for multiple Euler-Lagrange systems (MELSs) considering external disturbances and system uncertainties. First, we design a virtual network and propose a controller for all virtual nodes moving to the convex hull formed by all leaders. Then, we propose an adaptive tracking algorithm which combines a continuous robust integral of the sign of the error (RISE) feedback element and a neural network-based (NN-based) feedforward element to guarantee that each follower semi-globally asymptotically track the state of the corresponding virtual node. Apart from this, a smooth projection algorithm is ulitized to ensure that training values of NN weight matrices are bounded. Hence, the MELSs can achieve containment control. Furthermore, criteria for addressing the above model-independent containment control problem are given by the theoretical derivation. Finally, the correctness of the presented model-independent containment control method is checked out by a numerical simulation.